Overview

Brought to you by YData

Dataset statistics

Number of variables223
Number of observations584592
Missing cells90298403
Missing cells (%)69.3%
Total size in memory982.9 MiB
Average record size in memory1.7 KiB

Variable types

Numeric22
Unsupported127
Text70
Boolean4

Dataset

DescriptionBirds NMNH Extant Specimen Records 0054887-241126133413365
URLhttps://doi.org/10.15468/dl.2en7ue

Alerts

license has constant value "CC0_1_0" Constant
publisher has constant value "National Museum of Natural History, Smithsonian Institution" Constant
institutionID has constant value "urn:lsid:biocol.org:col:34871" Constant
collectionID has constant value "urn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893" Constant
institutionCode has constant value "USNM" Constant
collectionCode has constant value "BIRDS" Constant
datasetName has constant value "NMNH Extant Biology" Constant
basisOfRecord has constant value "PRESERVED_SPECIMEN" Constant
occurrenceStatus has constant value "PRESENT" Constant
kingdom has constant value "Animalia" Constant
phylum has constant value "Chordata" Constant
class has constant value "Aves" Constant
datasetKey has constant value "821cc27a-e3bb-4bc5-ac34-89ada245069d" Constant
publishingCountry has constant value "US" Constant
kingdomKey has constant value "1" Constant
phylumKey has constant value "44.0" Constant
classKey has constant value "212.0" Constant
protocol has constant value "EML" Constant
lastCrawled has constant value "2024-12-02T11:48:23.416Z" Constant
publishedByGbifRegion has constant value "NORTH_AMERICA" Constant
hasCoordinate is highly imbalanced (72.2%) Imbalance
hasGeospatialIssues is highly imbalanced (99.0%) Imbalance
isSequenced is highly imbalanced (93.5%) Imbalance
accessRights has 584592 (100.0%) missing values Missing
bibliographicCitation has 584592 (100.0%) missing values Missing
language has 584592 (100.0%) missing values Missing
references has 584592 (100.0%) missing values Missing
rightsHolder has 584592 (100.0%) missing values Missing
type has 584592 (100.0%) missing values Missing
datasetID has 584592 (100.0%) missing values Missing
ownerInstitutionCode has 584592 (100.0%) missing values Missing
informationWithheld has 584592 (100.0%) missing values Missing
dataGeneralizations has 584592 (100.0%) missing values Missing
dynamicProperties has 584592 (100.0%) missing values Missing
recordNumber has 584474 (> 99.9%) missing values Missing
recordedBy has 7123 (1.2%) missing values Missing
recordedByID has 584592 (100.0%) missing values Missing
organismQuantity has 584592 (100.0%) missing values Missing
organismQuantityType has 584592 (100.0%) missing values Missing
sex has 112304 (19.2%) missing values Missing
lifeStage has 459507 (78.6%) missing values Missing
reproductiveCondition has 584592 (100.0%) missing values Missing
caste has 584592 (100.0%) missing values Missing
behavior has 584592 (100.0%) missing values Missing
vitality has 584592 (100.0%) missing values Missing
establishmentMeans has 584592 (100.0%) missing values Missing
degreeOfEstablishment has 584592 (100.0%) missing values Missing
pathway has 584592 (100.0%) missing values Missing
georeferenceVerificationStatus has 584592 (100.0%) missing values Missing
disposition has 584592 (100.0%) missing values Missing
associatedOccurrences has 584592 (100.0%) missing values Missing
associatedReferences has 584592 (100.0%) missing values Missing
associatedSequences has 580105 (99.2%) missing values Missing
associatedTaxa has 584592 (100.0%) missing values Missing
otherCatalogNumbers has 584592 (100.0%) missing values Missing
occurrenceRemarks has 572414 (97.9%) missing values Missing
organismID has 584592 (100.0%) missing values Missing
organismName has 584592 (100.0%) missing values Missing
organismScope has 584592 (100.0%) missing values Missing
associatedOrganisms has 584592 (100.0%) missing values Missing
previousIdentifications has 584592 (100.0%) missing values Missing
organismRemarks has 584592 (100.0%) missing values Missing
materialEntityID has 584592 (100.0%) missing values Missing
materialEntityRemarks has 584592 (100.0%) missing values Missing
verbatimLabel has 584592 (100.0%) missing values Missing
materialSampleID has 584592 (100.0%) missing values Missing
eventID has 584592 (100.0%) missing values Missing
parentEventID has 584592 (100.0%) missing values Missing
eventType has 584592 (100.0%) missing values Missing
fieldNumber has 584592 (100.0%) missing values Missing
eventDate has 41361 (7.1%) missing values Missing
eventTime has 584592 (100.0%) missing values Missing
startDayOfYear has 74069 (12.7%) missing values Missing
endDayOfYear has 74069 (12.7%) missing values Missing
year has 41376 (7.1%) missing values Missing
month has 53877 (9.2%) missing values Missing
day has 74434 (12.7%) missing values Missing
verbatimEventDate has 235442 (40.3%) missing values Missing
habitat has 567355 (97.1%) missing values Missing
samplingProtocol has 584592 (100.0%) missing values Missing
sampleSizeValue has 584592 (100.0%) missing values Missing
sampleSizeUnit has 584592 (100.0%) missing values Missing
samplingEffort has 584592 (100.0%) missing values Missing
fieldNotes has 584592 (100.0%) missing values Missing
eventRemarks has 584592 (100.0%) missing values Missing
locationID has 584592 (100.0%) missing values Missing
higherGeographyID has 584592 (100.0%) missing values Missing
continent has 27500 (4.7%) missing values Missing
waterBody has 558515 (95.5%) missing values Missing
islandGroup has 584592 (100.0%) missing values Missing
island has 584592 (100.0%) missing values Missing
stateProvince has 93871 (16.1%) missing values Missing
county has 353572 (60.5%) missing values Missing
municipality has 584592 (100.0%) missing values Missing
locality has 107551 (18.4%) missing values Missing
verbatimLocality has 584592 (100.0%) missing values Missing
verbatimElevation has 583323 (99.8%) missing values Missing
verticalDatum has 584592 (100.0%) missing values Missing
verbatimDepth has 584592 (100.0%) missing values Missing
minimumDistanceAboveSurfaceInMeters has 584592 (100.0%) missing values Missing
maximumDistanceAboveSurfaceInMeters has 584592 (100.0%) missing values Missing
locationAccordingTo has 584592 (100.0%) missing values Missing
locationRemarks has 584592 (100.0%) missing values Missing
decimalLatitude has 556566 (95.2%) missing values Missing
decimalLongitude has 556566 (95.2%) missing values Missing
coordinateUncertaintyInMeters has 584592 (100.0%) missing values Missing
coordinatePrecision has 584592 (100.0%) missing values Missing
pointRadiusSpatialFit has 584592 (100.0%) missing values Missing
verbatimCoordinateSystem has 567281 (97.0%) missing values Missing
verbatimSRS has 584592 (100.0%) missing values Missing
footprintWKT has 584592 (100.0%) missing values Missing
footprintSRS has 584592 (100.0%) missing values Missing
footprintSpatialFit has 584592 (100.0%) missing values Missing
georeferencedBy has 584592 (100.0%) missing values Missing
georeferencedDate has 584592 (100.0%) missing values Missing
georeferenceProtocol has 583342 (99.8%) missing values Missing
georeferenceSources has 584592 (100.0%) missing values Missing
georeferenceRemarks has 584592 (100.0%) missing values Missing
geologicalContextID has 584592 (100.0%) missing values Missing
earliestEonOrLowestEonothem has 584592 (100.0%) missing values Missing
latestEonOrHighestEonothem has 584592 (100.0%) missing values Missing
earliestEraOrLowestErathem has 584592 (100.0%) missing values Missing
latestEraOrHighestErathem has 584592 (100.0%) missing values Missing
earliestPeriodOrLowestSystem has 584592 (100.0%) missing values Missing
latestPeriodOrHighestSystem has 584592 (100.0%) missing values Missing
earliestEpochOrLowestSeries has 584592 (100.0%) missing values Missing
latestEpochOrHighestSeries has 584592 (100.0%) missing values Missing
earliestAgeOrLowestStage has 584592 (100.0%) missing values Missing
latestAgeOrHighestStage has 584592 (100.0%) missing values Missing
lowestBiostratigraphicZone has 584592 (100.0%) missing values Missing
highestBiostratigraphicZone has 584592 (100.0%) missing values Missing
lithostratigraphicTerms has 584592 (100.0%) missing values Missing
group has 584592 (100.0%) missing values Missing
formation has 584592 (100.0%) missing values Missing
member has 584592 (100.0%) missing values Missing
bed has 584592 (100.0%) missing values Missing
identificationID has 584592 (100.0%) missing values Missing
verbatimIdentification has 584592 (100.0%) missing values Missing
identificationQualifier has 583894 (99.9%) missing values Missing
typeStatus has 580632 (99.3%) missing values Missing
identifiedBy has 581206 (99.4%) missing values Missing
identifiedByID has 584592 (100.0%) missing values Missing
dateIdentified has 584592 (100.0%) missing values Missing
identificationReferences has 584592 (100.0%) missing values Missing
identificationVerificationStatus has 584592 (100.0%) missing values Missing
identificationRemarks has 584592 (100.0%) missing values Missing
taxonID has 584592 (100.0%) missing values Missing
scientificNameID has 584592 (100.0%) missing values Missing
parentNameUsageID has 584592 (100.0%) missing values Missing
originalNameUsageID has 584592 (100.0%) missing values Missing
nameAccordingToID has 584592 (100.0%) missing values Missing
namePublishedInID has 584592 (100.0%) missing values Missing
taxonConceptID has 584592 (100.0%) missing values Missing
acceptedNameUsage has 584592 (100.0%) missing values Missing
parentNameUsage has 584592 (100.0%) missing values Missing
originalNameUsage has 584592 (100.0%) missing values Missing
nameAccordingTo has 584592 (100.0%) missing values Missing
namePublishedIn has 584592 (100.0%) missing values Missing
namePublishedInYear has 584592 (100.0%) missing values Missing
superfamily has 584592 (100.0%) missing values Missing
subfamily has 584592 (100.0%) missing values Missing
tribe has 584592 (100.0%) missing values Missing
subtribe has 584592 (100.0%) missing values Missing
subgenus has 584592 (100.0%) missing values Missing
infragenericEpithet has 584592 (100.0%) missing values Missing
specificEpithet has 7917 (1.4%) missing values Missing
infraspecificEpithet has 308675 (52.8%) missing values Missing
cultivarEpithet has 584592 (100.0%) missing values Missing
verbatimTaxonRank has 584592 (100.0%) missing values Missing
vernacularName has 584592 (100.0%) missing values Missing
nomenclaturalCode has 584592 (100.0%) missing values Missing
nomenclaturalStatus has 584592 (100.0%) missing values Missing
taxonRemarks has 584592 (100.0%) missing values Missing
elevation has 498000 (85.2%) missing values Missing
elevationAccuracy has 574752 (98.3%) missing values Missing
depth has 584592 (100.0%) missing values Missing
depthAccuracy has 584592 (100.0%) missing values Missing
distanceFromCentroidInMeters has 584584 (> 99.9%) missing values Missing
mediaType has 26095 (4.5%) missing values Missing
subgenusKey has 584592 (100.0%) missing values Missing
speciesKey has 7853 (1.3%) missing values Missing
species has 7853 (1.3%) missing values Missing
typifiedName has 584592 (100.0%) missing values Missing
relativeOrganismQuantity has 584592 (100.0%) missing values Missing
projectId has 584592 (100.0%) missing values Missing
gbifRegion has 19462 (3.3%) missing values Missing
level0Gid has 562100 (96.2%) missing values Missing
level0Name has 562100 (96.2%) missing values Missing
level1Gid has 562129 (96.2%) missing values Missing
level1Name has 562129 (96.2%) missing values Missing
level2Gid has 562935 (96.3%) missing values Missing
level2Name has 563182 (96.3%) missing values Missing
level3Gid has 575359 (98.4%) missing values Missing
level3Name has 576369 (98.6%) missing values Missing
iucnRedListCategory has 273793 (46.8%) missing values Missing
individualCount is highly skewed (γ1 = 24.10540025) Skewed
gbifID has unique values Unique
occurrenceID has unique values Unique
catalogNumber has unique values Unique
accessRights is an unsupported type, check if it needs cleaning or further analysis Unsupported
bibliographicCitation is an unsupported type, check if it needs cleaning or further analysis Unsupported
language is an unsupported type, check if it needs cleaning or further analysis Unsupported
references is an unsupported type, check if it needs cleaning or further analysis Unsupported
rightsHolder is an unsupported type, check if it needs cleaning or further analysis Unsupported
type is an unsupported type, check if it needs cleaning or further analysis Unsupported
datasetID is an unsupported type, check if it needs cleaning or further analysis Unsupported
ownerInstitutionCode is an unsupported type, check if it needs cleaning or further analysis Unsupported
informationWithheld is an unsupported type, check if it needs cleaning or further analysis Unsupported
dataGeneralizations is an unsupported type, check if it needs cleaning or further analysis Unsupported
dynamicProperties is an unsupported type, check if it needs cleaning or further analysis Unsupported
recordedByID is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismQuantity is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismQuantityType is an unsupported type, check if it needs cleaning or further analysis Unsupported
reproductiveCondition is an unsupported type, check if it needs cleaning or further analysis Unsupported
caste is an unsupported type, check if it needs cleaning or further analysis Unsupported
behavior is an unsupported type, check if it needs cleaning or further analysis Unsupported
vitality is an unsupported type, check if it needs cleaning or further analysis Unsupported
establishmentMeans is an unsupported type, check if it needs cleaning or further analysis Unsupported
degreeOfEstablishment is an unsupported type, check if it needs cleaning or further analysis Unsupported
pathway is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferenceVerificationStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
disposition is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedOccurrences is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedReferences is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedTaxa is an unsupported type, check if it needs cleaning or further analysis Unsupported
otherCatalogNumbers is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismID is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismName is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismScope is an unsupported type, check if it needs cleaning or further analysis Unsupported
associatedOrganisms is an unsupported type, check if it needs cleaning or further analysis Unsupported
previousIdentifications is an unsupported type, check if it needs cleaning or further analysis Unsupported
organismRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialEntityID is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialEntityRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimLabel is an unsupported type, check if it needs cleaning or further analysis Unsupported
materialSampleID is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventID is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentEventID is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventType is an unsupported type, check if it needs cleaning or further analysis Unsupported
fieldNumber is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventTime is an unsupported type, check if it needs cleaning or further analysis Unsupported
samplingProtocol is an unsupported type, check if it needs cleaning or further analysis Unsupported
sampleSizeValue is an unsupported type, check if it needs cleaning or further analysis Unsupported
sampleSizeUnit is an unsupported type, check if it needs cleaning or further analysis Unsupported
samplingEffort is an unsupported type, check if it needs cleaning or further analysis Unsupported
fieldNotes is an unsupported type, check if it needs cleaning or further analysis Unsupported
eventRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationID is an unsupported type, check if it needs cleaning or further analysis Unsupported
higherGeographyID is an unsupported type, check if it needs cleaning or further analysis Unsupported
islandGroup is an unsupported type, check if it needs cleaning or further analysis Unsupported
island is an unsupported type, check if it needs cleaning or further analysis Unsupported
municipality is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimLocality is an unsupported type, check if it needs cleaning or further analysis Unsupported
verticalDatum is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimDepth is an unsupported type, check if it needs cleaning or further analysis Unsupported
minimumDistanceAboveSurfaceInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
maximumDistanceAboveSurfaceInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationAccordingTo is an unsupported type, check if it needs cleaning or further analysis Unsupported
locationRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
coordinateUncertaintyInMeters is an unsupported type, check if it needs cleaning or further analysis Unsupported
coordinatePrecision is an unsupported type, check if it needs cleaning or further analysis Unsupported
pointRadiusSpatialFit is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimSRS is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintWKT is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintSRS is an unsupported type, check if it needs cleaning or further analysis Unsupported
footprintSpatialFit is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferencedBy is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferencedDate is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferenceSources is an unsupported type, check if it needs cleaning or further analysis Unsupported
georeferenceRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
geologicalContextID is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestEonOrLowestEonothem is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestEonOrHighestEonothem is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestEraOrLowestErathem is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestEraOrHighestErathem is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestPeriodOrLowestSystem is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestPeriodOrHighestSystem is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestEpochOrLowestSeries is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestEpochOrHighestSeries is an unsupported type, check if it needs cleaning or further analysis Unsupported
earliestAgeOrLowestStage is an unsupported type, check if it needs cleaning or further analysis Unsupported
latestAgeOrHighestStage is an unsupported type, check if it needs cleaning or further analysis Unsupported
lowestBiostratigraphicZone is an unsupported type, check if it needs cleaning or further analysis Unsupported
highestBiostratigraphicZone is an unsupported type, check if it needs cleaning or further analysis Unsupported
lithostratigraphicTerms is an unsupported type, check if it needs cleaning or further analysis Unsupported
group is an unsupported type, check if it needs cleaning or further analysis Unsupported
formation is an unsupported type, check if it needs cleaning or further analysis Unsupported
member is an unsupported type, check if it needs cleaning or further analysis Unsupported
bed is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationID is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimIdentification is an unsupported type, check if it needs cleaning or further analysis Unsupported
identifiedByID is an unsupported type, check if it needs cleaning or further analysis Unsupported
dateIdentified is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationReferences is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationVerificationStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
identificationRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonID is an unsupported type, check if it needs cleaning or further analysis Unsupported
scientificNameID is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentNameUsageID is an unsupported type, check if it needs cleaning or further analysis Unsupported
originalNameUsageID is an unsupported type, check if it needs cleaning or further analysis Unsupported
nameAccordingToID is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedInID is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonConceptID is an unsupported type, check if it needs cleaning or further analysis Unsupported
acceptedNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
parentNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
originalNameUsage is an unsupported type, check if it needs cleaning or further analysis Unsupported
nameAccordingTo is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedIn is an unsupported type, check if it needs cleaning or further analysis Unsupported
namePublishedInYear is an unsupported type, check if it needs cleaning or further analysis Unsupported
superfamily is an unsupported type, check if it needs cleaning or further analysis Unsupported
subfamily is an unsupported type, check if it needs cleaning or further analysis Unsupported
tribe is an unsupported type, check if it needs cleaning or further analysis Unsupported
subtribe is an unsupported type, check if it needs cleaning or further analysis Unsupported
subgenus is an unsupported type, check if it needs cleaning or further analysis Unsupported
infragenericEpithet is an unsupported type, check if it needs cleaning or further analysis Unsupported
cultivarEpithet is an unsupported type, check if it needs cleaning or further analysis Unsupported
verbatimTaxonRank is an unsupported type, check if it needs cleaning or further analysis Unsupported
vernacularName is an unsupported type, check if it needs cleaning or further analysis Unsupported
nomenclaturalCode is an unsupported type, check if it needs cleaning or further analysis Unsupported
nomenclaturalStatus is an unsupported type, check if it needs cleaning or further analysis Unsupported
taxonRemarks is an unsupported type, check if it needs cleaning or further analysis Unsupported
depth is an unsupported type, check if it needs cleaning or further analysis Unsupported
depthAccuracy is an unsupported type, check if it needs cleaning or further analysis Unsupported
subgenusKey is an unsupported type, check if it needs cleaning or further analysis Unsupported
typifiedName is an unsupported type, check if it needs cleaning or further analysis Unsupported
relativeOrganismQuantity is an unsupported type, check if it needs cleaning or further analysis Unsupported
projectId is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2025-01-07 15:47:43.229622
Analysis finished2025-01-07 15:48:00.890322
Duration17.66 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

gbifID
Real number (ℝ)

Unique 

Distinct584592
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1549641617
Minimum1317202470
Maximum4987328277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:00.923823image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1317202470
5-th percentile1317543209
Q11318923304
median1320638876
Q31322357759
95-th percentile3357307531
Maximum4987328277
Range3670125807
Interquartile range (IQR)3434454.5

Descriptive statistics

Standard deviation715523530.6
Coefficient of variation (CV)0.4617348441
Kurtosis12.41832031
Mean1549641617
Median Absolute Deviation (MAD)1717294.5
Skewness3.593527857
Sum9.059080924 × 1014
Variance5.119739229 × 1017
MonotonicityNot monotonic
2025-01-07T10:48:00.989024image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1321371489 1
 
< 0.1%
1321366979 1
 
< 0.1%
2592245118 1
 
< 0.1%
1321364594 1
 
< 0.1%
1321362937 1
 
< 0.1%
1321362121 1
 
< 0.1%
1321360093 1
 
< 0.1%
1321359973 1
 
< 0.1%
1321357813 1
 
< 0.1%
1456329024 1
 
< 0.1%
Other values (584582) 584582
> 99.9%
ValueCountFrequency (%)
1317202470 1
< 0.1%
1317202471 1
< 0.1%
1317202480 1
< 0.1%
1317202484 1
< 0.1%
1317202493 1
< 0.1%
ValueCountFrequency (%)
4987328277 1
< 0.1%
4987328253 1
< 0.1%
4987328200 1
< 0.1%
4987328183 1
< 0.1%
4987328096 1
< 0.1%

accessRights
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

bibliographicCitation
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

language
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

license
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:01.032542image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters4092144
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCC0_1_0
2nd rowCC0_1_0
3rd rowCC0_1_0
4th rowCC0_1_0
5th rowCC0_1_0
ValueCountFrequency (%)
cc0_1_0 584592
100.0%
2025-01-07T10:48:01.122309image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 1169184
28.6%
0 1169184
28.6%
_ 1169184
28.6%
1 584592
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4092144
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 1169184
28.6%
0 1169184
28.6%
_ 1169184
28.6%
1 584592
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4092144
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 1169184
28.6%
0 1169184
28.6%
_ 1169184
28.6%
1 584592
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4092144
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 1169184
28.6%
0 1169184
28.6%
_ 1169184
28.6%
1 584592
14.3%
Distinct11792
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:01.240987image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters11691840
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4737 ?
Unique (%)0.8%

Sample

1st row2024-03-26T12:49:00Z
2nd row2022-07-12T14:29:00Z
3rd row2022-04-29T16:16:00Z
4th row2022-04-05T14:20:00Z
5th row2022-09-22T21:27:00Z
ValueCountFrequency (%)
2024-09-19t15:58:00z 8050
 
1.4%
2024-09-19t15:59:00z 7282
 
1.2%
2024-09-19t15:57:00z 6771
 
1.2%
2024-11-12t09:38:00z 6108
 
1.0%
2024-09-19t15:43:00z 3407
 
0.6%
2024-09-19t16:00:00z 2927
 
0.5%
2022-09-22t21:42:00z 2178
 
0.4%
2022-09-22t21:59:00z 2177
 
0.4%
2022-09-22t20:03:00z 2168
 
0.4%
2022-09-22t21:51:00z 2164
 
0.4%
Other values (11782) 541360
92.6%
2025-01-07T10:48:01.430364image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2854206
24.4%
0 2776194
23.7%
- 1169184
10.0%
: 1169184
10.0%
1 800219
 
6.8%
T 584592
 
5.0%
Z 584592
 
5.0%
9 465374
 
4.0%
4 411253
 
3.5%
5 256891
 
2.2%
Other values (4) 620151
 
5.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11691840
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2854206
24.4%
0 2776194
23.7%
- 1169184
10.0%
: 1169184
10.0%
1 800219
 
6.8%
T 584592
 
5.0%
Z 584592
 
5.0%
9 465374
 
4.0%
4 411253
 
3.5%
5 256891
 
2.2%
Other values (4) 620151
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11691840
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2854206
24.4%
0 2776194
23.7%
- 1169184
10.0%
: 1169184
10.0%
1 800219
 
6.8%
T 584592
 
5.0%
Z 584592
 
5.0%
9 465374
 
4.0%
4 411253
 
3.5%
5 256891
 
2.2%
Other values (4) 620151
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11691840
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2854206
24.4%
0 2776194
23.7%
- 1169184
10.0%
: 1169184
10.0%
1 800219
 
6.8%
T 584592
 
5.0%
Z 584592
 
5.0%
9 465374
 
4.0%
4 411253
 
3.5%
5 256891
 
2.2%
Other values (4) 620151
 
5.3%

publisher
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:01.502326image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length59
Median length59
Mean length59
Min length59

Characters and Unicode

Total characters34490928
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNational Museum of Natural History, Smithsonian Institution
2nd rowNational Museum of Natural History, Smithsonian Institution
3rd rowNational Museum of Natural History, Smithsonian Institution
4th rowNational Museum of Natural History, Smithsonian Institution
5th rowNational Museum of Natural History, Smithsonian Institution
ValueCountFrequency (%)
national 584592
14.3%
museum 584592
14.3%
of 584592
14.3%
natural 584592
14.3%
history 584592
14.3%
smithsonian 584592
14.3%
institution 584592
14.3%
2025-01-07T10:48:01.611313image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 4092144
11.9%
i 3507552
10.2%
3507552
10.2%
o 2922960
 
8.5%
a 2922960
 
8.5%
n 2922960
 
8.5%
s 2338368
 
6.8%
u 2338368
 
6.8%
N 1169184
 
3.4%
m 1169184
 
3.4%
Other values (11) 7599696
22.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 34490928
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 4092144
11.9%
i 3507552
10.2%
3507552
10.2%
o 2922960
 
8.5%
a 2922960
 
8.5%
n 2922960
 
8.5%
s 2338368
 
6.8%
u 2338368
 
6.8%
N 1169184
 
3.4%
m 1169184
 
3.4%
Other values (11) 7599696
22.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 34490928
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 4092144
11.9%
i 3507552
10.2%
3507552
10.2%
o 2922960
 
8.5%
a 2922960
 
8.5%
n 2922960
 
8.5%
s 2338368
 
6.8%
u 2338368
 
6.8%
N 1169184
 
3.4%
m 1169184
 
3.4%
Other values (11) 7599696
22.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 34490928
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 4092144
11.9%
i 3507552
10.2%
3507552
10.2%
o 2922960
 
8.5%
a 2922960
 
8.5%
n 2922960
 
8.5%
s 2338368
 
6.8%
u 2338368
 
6.8%
N 1169184
 
3.4%
m 1169184
 
3.4%
Other values (11) 7599696
22.0%

references
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

rightsHolder
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

type
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:01.666317image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters16953168
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:lsid:biocol.org:col:34871
2nd rowurn:lsid:biocol.org:col:34871
3rd rowurn:lsid:biocol.org:col:34871
4th rowurn:lsid:biocol.org:col:34871
5th rowurn:lsid:biocol.org:col:34871
ValueCountFrequency (%)
urn:lsid:biocol.org:col:34871 584592
100.0%
2025-01-07T10:48:01.768831image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2338368
13.8%
: 2338368
13.8%
l 1753776
 
10.3%
r 1169184
 
6.9%
c 1169184
 
6.9%
i 1169184
 
6.9%
u 584592
 
3.4%
s 584592
 
3.4%
d 584592
 
3.4%
n 584592
 
3.4%
Other values (8) 4676736
27.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16953168
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2338368
13.8%
: 2338368
13.8%
l 1753776
 
10.3%
r 1169184
 
6.9%
c 1169184
 
6.9%
i 1169184
 
6.9%
u 584592
 
3.4%
s 584592
 
3.4%
d 584592
 
3.4%
n 584592
 
3.4%
Other values (8) 4676736
27.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16953168
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2338368
13.8%
: 2338368
13.8%
l 1753776
 
10.3%
r 1169184
 
6.9%
c 1169184
 
6.9%
i 1169184
 
6.9%
u 584592
 
3.4%
s 584592
 
3.4%
d 584592
 
3.4%
n 584592
 
3.4%
Other values (8) 4676736
27.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16953168
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2338368
13.8%
: 2338368
13.8%
l 1753776
 
10.3%
r 1169184
 
6.9%
c 1169184
 
6.9%
i 1169184
 
6.9%
u 584592
 
3.4%
s 584592
 
3.4%
d 584592
 
3.4%
n 584592
 
3.4%
Other values (8) 4676736
27.6%

collectionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:01.824391image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters26306640
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893
2nd rowurn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893
3rd rowurn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893
4th rowurn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893
5th rowurn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893
ValueCountFrequency (%)
urn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893 584592
100.0%
2025-01-07T10:48:01.928297image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 3507552
13.3%
d 2922960
11.1%
9 2338368
 
8.9%
- 2338368
 
8.9%
2 1753776
 
6.7%
8 1753776
 
6.7%
u 1753776
 
6.7%
: 1169184
 
4.4%
a 1169184
 
4.4%
7 1169184
 
4.4%
Other values (10) 6430512
24.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26306640
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 3507552
13.3%
d 2922960
11.1%
9 2338368
 
8.9%
- 2338368
 
8.9%
2 1753776
 
6.7%
8 1753776
 
6.7%
u 1753776
 
6.7%
: 1169184
 
4.4%
a 1169184
 
4.4%
7 1169184
 
4.4%
Other values (10) 6430512
24.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26306640
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 3507552
13.3%
d 2922960
11.1%
9 2338368
 
8.9%
- 2338368
 
8.9%
2 1753776
 
6.7%
8 1753776
 
6.7%
u 1753776
 
6.7%
: 1169184
 
4.4%
a 1169184
 
4.4%
7 1169184
 
4.4%
Other values (10) 6430512
24.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26306640
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 3507552
13.3%
d 2922960
11.1%
9 2338368
 
8.9%
- 2338368
 
8.9%
2 1753776
 
6.7%
8 1753776
 
6.7%
u 1753776
 
6.7%
: 1169184
 
4.4%
a 1169184
 
4.4%
7 1169184
 
4.4%
Other values (10) 6430512
24.4%

datasetID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

institutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:01.967300image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2338368
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSNM
2nd rowUSNM
3rd rowUSNM
4th rowUSNM
5th rowUSNM
ValueCountFrequency (%)
usnm 584592
100.0%
2025-01-07T10:48:02.056392image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 584592
25.0%
S 584592
25.0%
N 584592
25.0%
M 584592
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2338368
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 584592
25.0%
S 584592
25.0%
N 584592
25.0%
M 584592
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2338368
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 584592
25.0%
S 584592
25.0%
N 584592
25.0%
M 584592
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2338368
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 584592
25.0%
S 584592
25.0%
N 584592
25.0%
M 584592
25.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:02.097374image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2922960
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBIRDS
2nd rowBIRDS
3rd rowBIRDS
4th rowBIRDS
5th rowBIRDS
ValueCountFrequency (%)
birds 584592
100.0%
2025-01-07T10:48:02.253865image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 584592
20.0%
I 584592
20.0%
R 584592
20.0%
D 584592
20.0%
S 584592
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2922960
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
B 584592
20.0%
I 584592
20.0%
R 584592
20.0%
D 584592
20.0%
S 584592
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2922960
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
B 584592
20.0%
I 584592
20.0%
R 584592
20.0%
D 584592
20.0%
S 584592
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2922960
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
B 584592
20.0%
I 584592
20.0%
R 584592
20.0%
D 584592
20.0%
S 584592
20.0%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:02.296355image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11107248
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Extant Biology
2nd rowNMNH Extant Biology
3rd rowNMNH Extant Biology
4th rowNMNH Extant Biology
5th rowNMNH Extant Biology
ValueCountFrequency (%)
nmnh 584592
33.3%
extant 584592
33.3%
biology 584592
33.3%
2025-01-07T10:48:02.387500image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1169184
 
10.5%
t 1169184
 
10.5%
1169184
 
10.5%
o 1169184
 
10.5%
H 584592
 
5.3%
E 584592
 
5.3%
M 584592
 
5.3%
x 584592
 
5.3%
a 584592
 
5.3%
B 584592
 
5.3%
Other values (5) 2922960
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11107248
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 1169184
 
10.5%
t 1169184
 
10.5%
1169184
 
10.5%
o 1169184
 
10.5%
H 584592
 
5.3%
E 584592
 
5.3%
M 584592
 
5.3%
x 584592
 
5.3%
a 584592
 
5.3%
B 584592
 
5.3%
Other values (5) 2922960
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11107248
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 1169184
 
10.5%
t 1169184
 
10.5%
1169184
 
10.5%
o 1169184
 
10.5%
H 584592
 
5.3%
E 584592
 
5.3%
M 584592
 
5.3%
x 584592
 
5.3%
a 584592
 
5.3%
B 584592
 
5.3%
Other values (5) 2922960
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11107248
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 1169184
 
10.5%
t 1169184
 
10.5%
1169184
 
10.5%
o 1169184
 
10.5%
H 584592
 
5.3%
E 584592
 
5.3%
M 584592
 
5.3%
x 584592
 
5.3%
a 584592
 
5.3%
B 584592
 
5.3%
Other values (5) 2922960
26.3%

ownerInstitutionCode
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

basisOfRecord
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:02.434008image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters10522656
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPRESERVED_SPECIMEN
2nd rowPRESERVED_SPECIMEN
3rd rowPRESERVED_SPECIMEN
4th rowPRESERVED_SPECIMEN
5th rowPRESERVED_SPECIMEN
ValueCountFrequency (%)
preserved_specimen 584592
100.0%
2025-01-07T10:48:02.536312image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 2922960
27.8%
P 1169184
 
11.1%
R 1169184
 
11.1%
S 1169184
 
11.1%
V 584592
 
5.6%
D 584592
 
5.6%
_ 584592
 
5.6%
C 584592
 
5.6%
I 584592
 
5.6%
M 584592
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10522656
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 2922960
27.8%
P 1169184
 
11.1%
R 1169184
 
11.1%
S 1169184
 
11.1%
V 584592
 
5.6%
D 584592
 
5.6%
_ 584592
 
5.6%
C 584592
 
5.6%
I 584592
 
5.6%
M 584592
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10522656
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 2922960
27.8%
P 1169184
 
11.1%
R 1169184
 
11.1%
S 1169184
 
11.1%
V 584592
 
5.6%
D 584592
 
5.6%
_ 584592
 
5.6%
C 584592
 
5.6%
I 584592
 
5.6%
M 584592
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10522656
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 2922960
27.8%
P 1169184
 
11.1%
R 1169184
 
11.1%
S 1169184
 
11.1%
V 584592
 
5.6%
D 584592
 
5.6%
_ 584592
 
5.6%
C 584592
 
5.6%
I 584592
 
5.6%
M 584592
 
5.6%

informationWithheld
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

dataGeneralizations
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

dynamicProperties
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

occurrenceID
Text

Unique 

Distinct584592
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:02.852248image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters36829296
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique584592 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/300075fa7-edd1-461a-9f08-e6ba501db28c
2nd rowhttp://n2t.net/ark:/65665/3000df15d-8cee-4e97-92ce-bb2a2eabd590
3rd rowhttp://n2t.net/ark:/65665/3ec08151f-42be-49b5-868b-d3deeddbd447
4th rowhttp://n2t.net/ark:/65665/30026d668-b659-45a3-8494-25f389913e98
5th rowhttp://n2t.net/ark:/65665/3003b6dd3-df37-400f-8ae6-e515ea9c2d04
ValueCountFrequency (%)
http://n2t.net/ark:/65665/3b872366d-fe3d-4592-a454-8b4c07271066 1
 
< 0.1%
http://n2t.net/ark:/65665/3b88499dc-9117-4901-a731-1f0632a534bd 1
 
< 0.1%
http://n2t.net/ark:/65665/3b8e9d312-ba4a-48bd-8ae9-d7cfac7e9ff6 1
 
< 0.1%
http://n2t.net/ark:/65665/3b8fcb6cc-afb5-4086-a0e3-56c0d3c15a07 1
 
< 0.1%
http://n2t.net/ark:/65665/3b90e2cbc-ea68-4d35-8173-45aa682655ff 1
 
< 0.1%
http://n2t.net/ark:/65665/3b94bb01f-460e-4898-9f7f-7f9580d1e27f 1
 
< 0.1%
http://n2t.net/ark:/65665/3b94c8b03-186f-450e-bb78-20418fa23055 1
 
< 0.1%
http://n2t.net/ark:/65665/3b9529f88-ace2-4467-87e2-021a8684e851 1
 
< 0.1%
http://n2t.net/ark:/65665/3b989cbce-7a29-4997-847d-32d024f80a2d 1
 
< 0.1%
http://n2t.net/ark:/65665/3b9a49be8-9d8f-46a0-824e-55eddf5e2ef3 1
 
< 0.1%
Other values (584582) 584582
> 99.9%
2025-01-07T10:48:03.231139image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 2922960
 
7.9%
6 2852045
 
7.7%
- 2338368
 
6.3%
t 2338368
 
6.3%
5 2265649
 
6.2%
a 1827322
 
5.0%
2 1681511
 
4.6%
3 1680550
 
4.6%
e 1680227
 
4.6%
4 1679992
 
4.6%
Other values (16) 15562304
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 36829296
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 2922960
 
7.9%
6 2852045
 
7.7%
- 2338368
 
6.3%
t 2338368
 
6.3%
5 2265649
 
6.2%
a 1827322
 
5.0%
2 1681511
 
4.6%
3 1680550
 
4.6%
e 1680227
 
4.6%
4 1679992
 
4.6%
Other values (16) 15562304
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 36829296
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 2922960
 
7.9%
6 2852045
 
7.7%
- 2338368
 
6.3%
t 2338368
 
6.3%
5 2265649
 
6.2%
a 1827322
 
5.0%
2 1681511
 
4.6%
3 1680550
 
4.6%
e 1680227
 
4.6%
4 1679992
 
4.6%
Other values (16) 15562304
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 36829296
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 2922960
 
7.9%
6 2852045
 
7.7%
- 2338368
 
6.3%
t 2338368
 
6.3%
5 2265649
 
6.2%
a 1827322
 
5.0%
2 1681511
 
4.6%
3 1680550
 
4.6%
e 1680227
 
4.6%
4 1679992
 
4.6%
Other values (16) 15562304
42.3%

catalogNumber
Text

Unique 

Distinct584592
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:03.692978image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.92067972
Min length6

Characters and Unicode

Total characters6384142
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique584592 ?
Unique (%)100.0%

Sample

1st rowUSNM A16396
2nd rowUSNM 101402
3rd rowUSNM B28085
4th rowUSNM 289875
5th rowUSNM 562118
ValueCountFrequency (%)
usnm 584592
50.0%
161935 1
 
< 0.1%
373126 1
 
< 0.1%
559814 1
 
< 0.1%
86018 1
 
< 0.1%
71706 1
 
< 0.1%
601464 1
 
< 0.1%
380926 1
 
< 0.1%
400497 1
 
< 0.1%
377013 1
 
< 0.1%
Other values (584583) 584583
50.0%
2025-01-07T10:48:04.163600image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 584592
 
9.2%
S 584592
 
9.2%
N 584592
 
9.2%
M 584592
 
9.2%
584592
 
9.2%
3 396623
 
6.2%
4 396155
 
6.2%
5 388165
 
6.1%
1 387443
 
6.1%
2 382727
 
6.0%
Other values (7) 1510069
23.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6384142
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 584592
 
9.2%
S 584592
 
9.2%
N 584592
 
9.2%
M 584592
 
9.2%
584592
 
9.2%
3 396623
 
6.2%
4 396155
 
6.2%
5 388165
 
6.1%
1 387443
 
6.1%
2 382727
 
6.0%
Other values (7) 1510069
23.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6384142
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 584592
 
9.2%
S 584592
 
9.2%
N 584592
 
9.2%
M 584592
 
9.2%
584592
 
9.2%
3 396623
 
6.2%
4 396155
 
6.2%
5 388165
 
6.1%
1 387443
 
6.1%
2 382727
 
6.0%
Other values (7) 1510069
23.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6384142
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 584592
 
9.2%
S 584592
 
9.2%
N 584592
 
9.2%
M 584592
 
9.2%
584592
 
9.2%
3 396623
 
6.2%
4 396155
 
6.2%
5 388165
 
6.1%
1 387443
 
6.1%
2 382727
 
6.0%
Other values (7) 1510069
23.7%

recordNumber
Text

Missing 

Distinct4
Distinct (%)3.4%
Missing584474
Missing (%)> 99.9%
Memory size4.5 MiB
2025-01-07T10:48:04.221661image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.059322034
Min length1

Characters and Unicode

Total characters125
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)2.5%

Sample

1st rowl
2nd rowl
3rd rowdu
4th rowl
5th rowl
ValueCountFrequency (%)
l 115
97.5%
du 1
 
0.8%
riley 1
 
0.8%
sta 1
 
0.8%
2025-01-07T10:48:04.322596image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 116
92.8%
d 1
 
0.8%
u 1
 
0.8%
r 1
 
0.8%
i 1
 
0.8%
e 1
 
0.8%
y 1
 
0.8%
s 1
 
0.8%
t 1
 
0.8%
a 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 125
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 116
92.8%
d 1
 
0.8%
u 1
 
0.8%
r 1
 
0.8%
i 1
 
0.8%
e 1
 
0.8%
y 1
 
0.8%
s 1
 
0.8%
t 1
 
0.8%
a 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 125
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 116
92.8%
d 1
 
0.8%
u 1
 
0.8%
r 1
 
0.8%
i 1
 
0.8%
e 1
 
0.8%
y 1
 
0.8%
s 1
 
0.8%
t 1
 
0.8%
a 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 125
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 116
92.8%
d 1
 
0.8%
u 1
 
0.8%
r 1
 
0.8%
i 1
 
0.8%
e 1
 
0.8%
y 1
 
0.8%
s 1
 
0.8%
t 1
 
0.8%
a 1
 
0.8%

recordedBy
Text

Missing 

Distinct13250
Distinct (%)2.3%
Missing7123
Missing (%)1.2%
Memory size4.5 MiB
2025-01-07T10:48:04.517062image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length60
Median length55
Mean length11.76426613
Min length1

Characters and Unicode

Total characters6793499
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6170 ?
Unique (%)1.1%

Sample

1st rowT. Page
2nd rowC. Worthen
3rd rowH. Lee
4th rowC. Sperry
5th rowC. Ross
ValueCountFrequency (%)
a 64567
 
4.8%
j 60293
 
4.5%
e 58464
 
4.4%
56508
 
4.2%
w 52970
 
4.0%
h 41937
 
3.1%
m 37812
 
2.8%
c 37330
 
2.8%
t 32505
 
2.4%
wetmore 32367
 
2.4%
Other values (7402) 863863
64.5%
2025-01-07T10:48:04.796479image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
761147
 
11.2%
. 558992
 
8.2%
e 547336
 
8.1%
r 485535
 
7.1%
o 389498
 
5.7%
n 353948
 
5.2%
a 303496
 
4.5%
l 299899
 
4.4%
i 264364
 
3.9%
t 245352
 
3.6%
Other values (55) 2583932
38.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6793499
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
761147
 
11.2%
. 558992
 
8.2%
e 547336
 
8.1%
r 485535
 
7.1%
o 389498
 
5.7%
n 353948
 
5.2%
a 303496
 
4.5%
l 299899
 
4.4%
i 264364
 
3.9%
t 245352
 
3.6%
Other values (55) 2583932
38.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6793499
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
761147
 
11.2%
. 558992
 
8.2%
e 547336
 
8.1%
r 485535
 
7.1%
o 389498
 
5.7%
n 353948
 
5.2%
a 303496
 
4.5%
l 299899
 
4.4%
i 264364
 
3.9%
t 245352
 
3.6%
Other values (55) 2583932
38.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6793499
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
761147
 
11.2%
. 558992
 
8.2%
e 547336
 
8.1%
r 485535
 
7.1%
o 389498
 
5.7%
n 353948
 
5.2%
a 303496
 
4.5%
l 299899
 
4.4%
i 264364
 
3.9%
t 245352
 
3.6%
Other values (55) 2583932
38.0%

recordedByID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

individualCount
Real number (ℝ)

Skewed 

Distinct49
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.130559433
Minimum1
Maximum133
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:04.874985image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum133
Range132
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8392867162
Coefficient of variation (CV)0.7423640826
Kurtosis1857.74983
Mean1.130559433
Median Absolute Deviation (MAD)0
Skewness24.10540025
Sum660916
Variance0.704402192
MonotonicityNot monotonic
2025-01-07T10:48:04.939914image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1 558309
95.5%
2 6799
 
1.2%
4 6794
 
1.2%
3 6435
 
1.1%
5 3136
 
0.5%
6 1204
 
0.2%
7 608
 
0.1%
8 374
 
0.1%
9 251
 
< 0.1%
10 169
 
< 0.1%
Other values (39) 513
 
0.1%
ValueCountFrequency (%)
1 558309
95.5%
2 6799
 
1.2%
3 6435
 
1.1%
4 6794
 
1.2%
5 3136
 
0.5%
ValueCountFrequency (%)
133 1
< 0.1%
81 1
< 0.1%
80 1
< 0.1%
70 1
< 0.1%
60 1
< 0.1%

organismQuantity
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

organismQuantityType
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

sex
Text

Missing 

Distinct2
Distinct (%)< 0.1%
Missing112304
Missing (%)19.2%
Memory size4.5 MiB
2025-01-07T10:48:04.980917image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.817674809
Min length4

Characters and Unicode

Total characters2275330
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMALE
2nd rowFEMALE
3rd rowMALE
4th rowMALE
5th rowMALE
ValueCountFrequency (%)
male 279199
59.1%
female 193089
40.9%
2025-01-07T10:48:05.081709image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 665377
29.2%
M 472288
20.8%
A 472288
20.8%
L 472288
20.8%
F 193089
 
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2275330
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 665377
29.2%
M 472288
20.8%
A 472288
20.8%
L 472288
20.8%
F 193089
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2275330
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 665377
29.2%
M 472288
20.8%
A 472288
20.8%
L 472288
20.8%
F 193089
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2275330
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 665377
29.2%
M 472288
20.8%
A 472288
20.8%
L 472288
20.8%
F 193089
 
8.5%

lifeStage
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing459507
Missing (%)78.6%
Memory size4.5 MiB
2025-01-07T10:48:05.125490image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.961034497
Min length5

Characters and Unicode

Total characters745636
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowImmature
2nd rowJuvenile
3rd rowAdult
4th rowAdult
5th rowAdult
ValueCountFrequency (%)
adult 81111
64.8%
immature 27828
 
22.2%
juvenile 10762
 
8.6%
chick 3709
 
3.0%
subadult 1382
 
1.1%
embryo 292
 
0.2%
nestling 1
 
< 0.1%
2025-01-07T10:48:05.220861image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
u 122465
16.4%
t 110322
14.8%
l 93256
12.5%
d 82493
11.1%
A 81111
10.9%
m 55948
7.5%
e 49353
6.6%
a 29210
 
3.9%
r 28120
 
3.8%
I 27828
 
3.7%
Other values (16) 65530
8.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 745636
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
u 122465
16.4%
t 110322
14.8%
l 93256
12.5%
d 82493
11.1%
A 81111
10.9%
m 55948
7.5%
e 49353
6.6%
a 29210
 
3.9%
r 28120
 
3.8%
I 27828
 
3.7%
Other values (16) 65530
8.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 745636
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
u 122465
16.4%
t 110322
14.8%
l 93256
12.5%
d 82493
11.1%
A 81111
10.9%
m 55948
7.5%
e 49353
6.6%
a 29210
 
3.9%
r 28120
 
3.8%
I 27828
 
3.7%
Other values (16) 65530
8.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 745636
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
u 122465
16.4%
t 110322
14.8%
l 93256
12.5%
d 82493
11.1%
A 81111
10.9%
m 55948
7.5%
e 49353
6.6%
a 29210
 
3.9%
r 28120
 
3.8%
I 27828
 
3.7%
Other values (16) 65530
8.8%

reproductiveCondition
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

caste
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

behavior
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

vitality
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

establishmentMeans
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

degreeOfEstablishment
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

pathway
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

georeferenceVerificationStatus
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

occurrenceStatus
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:05.262865image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters4092144
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPRESENT
2nd rowPRESENT
3rd rowPRESENT
4th rowPRESENT
5th rowPRESENT
ValueCountFrequency (%)
present 584592
100.0%
2025-01-07T10:48:05.353989image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 1169184
28.6%
P 584592
14.3%
R 584592
14.3%
S 584592
14.3%
N 584592
14.3%
T 584592
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4092144
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 1169184
28.6%
P 584592
14.3%
R 584592
14.3%
S 584592
14.3%
N 584592
14.3%
T 584592
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4092144
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 1169184
28.6%
P 584592
14.3%
R 584592
14.3%
S 584592
14.3%
N 584592
14.3%
T 584592
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4092144
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 1169184
28.6%
P 584592
14.3%
R 584592
14.3%
S 584592
14.3%
N 584592
14.3%
T 584592
14.3%
Distinct132
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:48:05.404053image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length76
Median length11
Mean length11.71096126
Min length6

Characters and Unicode

Total characters6846064
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)< 0.1%

Sample

1st rowSkin: Whole
2nd rowSkin: Whole
3rd rowEgg(s)
4th rowSkeleton: Whole
5th rowSkeleton: Whole
ValueCountFrequency (%)
whole 535339
45.8%
skin 470355
40.2%
skeleton 58626
 
5.0%
egg(s 33064
 
2.8%
fluid 32579
 
2.8%
partial 24616
 
2.1%
nest(s 4794
 
0.4%
feather(s 4784
 
0.4%
mounted 1952
 
0.2%
clutch 967
 
0.1%
Other values (7) 2530
 
0.2%
2025-01-07T10:48:05.524764image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 671417
9.8%
l 654016
9.6%
o 595917
8.7%
585020
8.5%
: 562892
8.2%
h 541090
7.9%
W 535338
7.8%
n 532123
7.8%
i 529352
7.7%
S 529335
7.7%
Other values (21) 1109564
16.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6846064
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 671417
9.8%
l 654016
9.6%
o 595917
8.7%
585020
8.5%
: 562892
8.2%
h 541090
7.9%
W 535338
7.8%
n 532123
7.8%
i 529352
7.7%
S 529335
7.7%
Other values (21) 1109564
16.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6846064
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 671417
9.8%
l 654016
9.6%
o 595917
8.7%
585020
8.5%
: 562892
8.2%
h 541090
7.9%
W 535338
7.8%
n 532123
7.8%
i 529352
7.7%
S 529335
7.7%
Other values (21) 1109564
16.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6846064
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 671417
9.8%
l 654016
9.6%
o 595917
8.7%
585020
8.5%
: 562892
8.2%
h 541090
7.9%
W 535338
7.8%
n 532123
7.8%
i 529352
7.7%
S 529335
7.7%
Other values (21) 1109564
16.2%

disposition
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

associatedOccurrences
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

associatedReferences
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

associatedSequences
Text

Missing 

Distinct4430
Distinct (%)98.7%
Missing580105
Missing (%)99.2%
Memory size4.5 MiB
2025-01-07T10:48:05.594469image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12558
Median length49
Mean length129.0780031
Min length49

Characters and Unicode

Total characters579173
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4421 ?
Unique (%)98.5%

Sample

1st rowhttps://www.ncbi.nlm.nih.gov/gquery?term=KM080095
2nd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=JQ176229
3rd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=JQ173910
4th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=KU722483
5th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=FJ547617;https://www.ncbi.nlm.nih.gov/gquery?term=FJ547732;https://www.ncbi.nlm.nih.gov/gquery?term=FJ547781;https://www.ncbi.nlm.nih.gov/gquery?term=FJ547782
ValueCountFrequency (%)
https://www.ncbi.nlm.nih.gov/gquery?term=prjna521985 34
 
0.8%
https://www.ncbi.nlm.nih.gov/gquery?term=ay273835 10
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=ay273864 8
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=ay273832 3
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj207364 3
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj207374 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj207379 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=mh778417 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=dq433197 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=jq445311;https://www.ncbi.nlm.nih.gov/gquery?term=mg682674;https://www.ncbi.nlm.nih.gov/gquery?term=mg682605;https://www.ncbi.nlm.nih.gov/gquery?term=mg682762;https://www.ncbi.nlm.nih.gov/gquery?term=mg682897 1
 
< 0.1%
Other values (4420) 4420
98.5%
2025-01-07T10:48:05.810050image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 46361
 
8.0%
/ 34770
 
6.0%
t 34770
 
6.0%
n 34770
 
6.0%
w 34770
 
6.0%
h 23180
 
4.0%
m 23180
 
4.0%
g 23180
 
4.0%
i 23180
 
4.0%
e 23180
 
4.0%
Other values (53) 277832
48.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 579173
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 46361
 
8.0%
/ 34770
 
6.0%
t 34770
 
6.0%
n 34770
 
6.0%
w 34770
 
6.0%
h 23180
 
4.0%
m 23180
 
4.0%
g 23180
 
4.0%
i 23180
 
4.0%
e 23180
 
4.0%
Other values (53) 277832
48.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 579173
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 46361
 
8.0%
/ 34770
 
6.0%
t 34770
 
6.0%
n 34770
 
6.0%
w 34770
 
6.0%
h 23180
 
4.0%
m 23180
 
4.0%
g 23180
 
4.0%
i 23180
 
4.0%
e 23180
 
4.0%
Other values (53) 277832
48.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 579173
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 46361
 
8.0%
/ 34770
 
6.0%
t 34770
 
6.0%
n 34770
 
6.0%
w 34770
 
6.0%
h 23180
 
4.0%
m 23180
 
4.0%
g 23180
 
4.0%
i 23180
 
4.0%
e 23180
 
4.0%
Other values (53) 277832
48.0%

associatedTaxa
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

otherCatalogNumbers
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

occurrenceRemarks
Text

Missing 

Distinct7341
Distinct (%)60.3%
Missing572414
Missing (%)97.9%
Memory size4.5 MiB
2025-01-07T10:48:06.009529image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6354
Median length555
Mean length50.68484152
Min length1

Characters and Unicode

Total characters617240
Distinct characters102
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6370 ?
Unique (%)52.3%

Sample

1st rowcarcass saved
2nd rowfertile
3rd rowA second soft part color is listed, but it is in French. It needs translated; the handwriting is somewhat smushed and hard to read. Appears to be "Patte et tour des yeux carminis." [Feet and eye ring carmine?]
4th rowbreeding
5th rowW.P. Taylor
ValueCountFrequency (%)
of 4593
 
4.4%
in 2349
 
2.2%
as 2209
 
2.1%
the 2118
 
2.0%
usnm 2055
 
2.0%
tag 1748
 
1.7%
specimens 1534
 
1.5%
cataloged 1516
 
1.4%
1422
 
1.4%
originally 1393
 
1.3%
Other values (10725) 84151
80.1%
2025-01-07T10:48:06.283646image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
92912
15.1%
e 51486
 
8.3%
a 37742
 
6.1%
n 34944
 
5.7%
o 33997
 
5.5%
i 32379
 
5.2%
t 32167
 
5.2%
s 26495
 
4.3%
r 25801
 
4.2%
l 22827
 
3.7%
Other values (92) 226490
36.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 617240
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
92912
15.1%
e 51486
 
8.3%
a 37742
 
6.1%
n 34944
 
5.7%
o 33997
 
5.5%
i 32379
 
5.2%
t 32167
 
5.2%
s 26495
 
4.3%
r 25801
 
4.2%
l 22827
 
3.7%
Other values (92) 226490
36.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 617240
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
92912
15.1%
e 51486
 
8.3%
a 37742
 
6.1%
n 34944
 
5.7%
o 33997
 
5.5%
i 32379
 
5.2%
t 32167
 
5.2%
s 26495
 
4.3%
r 25801
 
4.2%
l 22827
 
3.7%
Other values (92) 226490
36.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 617240
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
92912
15.1%
e 51486
 
8.3%
a 37742
 
6.1%
n 34944
 
5.7%
o 33997
 
5.5%
i 32379
 
5.2%
t 32167
 
5.2%
s 26495
 
4.3%
r 25801
 
4.2%
l 22827
 
3.7%
Other values (92) 226490
36.7%

organismID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

organismName
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

organismScope
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

associatedOrganisms
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

previousIdentifications
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

organismRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

materialEntityID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

materialEntityRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

verbatimLabel
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

materialSampleID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

eventID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

parentEventID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

eventType
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

fieldNumber
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

eventDate
Text

Missing 

Distinct51161
Distinct (%)9.4%
Missing41361
Missing (%)7.1%
Memory size4.5 MiB
2025-01-07T10:48:06.502680image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length10
Mean length9.758292513
Min length4

Characters and Unicode

Total characters5301007
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7962 ?
Unique (%)1.5%

Sample

1st row1859-05
2nd row1883-03-18
3rd row1895-05-26
4th row1924-08-06
5th row1987-04-09
ValueCountFrequency (%)
1865 620
 
0.1%
1877 533
 
0.1%
1966 478
 
0.1%
1926 419
 
0.1%
1939-07 366
 
0.1%
1937 360
 
0.1%
1936 281
 
0.1%
1884 276
 
0.1%
1888 253
 
< 0.1%
1881 250
 
< 0.1%
Other values (51151) 539395
99.3%
2025-01-07T10:48:06.784607image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1042086
19.7%
1 1031643
19.5%
0 807962
15.2%
9 611293
11.5%
2 400793
 
7.6%
8 308847
 
5.8%
6 249386
 
4.7%
3 225349
 
4.3%
5 223549
 
4.2%
4 216076
 
4.1%
Other values (2) 184023
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5301007
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 1042086
19.7%
1 1031643
19.5%
0 807962
15.2%
9 611293
11.5%
2 400793
 
7.6%
8 308847
 
5.8%
6 249386
 
4.7%
3 225349
 
4.3%
5 223549
 
4.2%
4 216076
 
4.1%
Other values (2) 184023
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5301007
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 1042086
19.7%
1 1031643
19.5%
0 807962
15.2%
9 611293
11.5%
2 400793
 
7.6%
8 308847
 
5.8%
6 249386
 
4.7%
3 225349
 
4.3%
5 223549
 
4.2%
4 216076
 
4.1%
Other values (2) 184023
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5301007
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 1042086
19.7%
1 1031643
19.5%
0 807962
15.2%
9 611293
11.5%
2 400793
 
7.6%
8 308847
 
5.8%
6 249386
 
4.7%
3 225349
 
4.3%
5 223549
 
4.2%
4 216076
 
4.1%
Other values (2) 184023
 
3.5%

eventTime
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

startDayOfYear
Real number (ℝ)

Missing 

Distinct366
Distinct (%)0.1%
Missing74069
Missing (%)12.7%
Infinite0
Infinite (%)0.0%
Mean169.2367885
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:06.861630image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25
Q195
median158
Q3243
95-th percentile337
Maximum366
Range365
Interquartile range (IQR)148

Descriptive statistics

Standard deviation95.01576313
Coefficient of variation (CV)0.5614368126
Kurtosis-0.8951480928
Mean169.2367885
Median Absolute Deviation (MAD)73
Skewness0.2500794283
Sum86399273
Variance9027.995243
MonotonicityNot monotonic
2025-01-07T10:48:06.923163image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140 2507
 
0.4%
141 2480
 
0.4%
134 2428
 
0.4%
135 2416
 
0.4%
150 2400
 
0.4%
142 2384
 
0.4%
136 2383
 
0.4%
166 2363
 
0.4%
139 2355
 
0.4%
132 2336
 
0.4%
Other values (356) 486471
83.2%
(Missing) 74069
 
12.7%
ValueCountFrequency (%)
1 1034
0.2%
2 809
0.1%
3 952
0.2%
4 946
0.2%
5 892
0.2%
ValueCountFrequency (%)
366 148
 
< 0.1%
365 801
0.1%
364 967
0.2%
363 984
0.2%
362 1035
0.2%

endDayOfYear
Real number (ℝ)

Missing 

Distinct366
Distinct (%)0.1%
Missing74069
Missing (%)12.7%
Infinite0
Infinite (%)0.0%
Mean169.245319
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:06.983670image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25
Q195
median159
Q3243
95-th percentile337
Maximum366
Range365
Interquartile range (IQR)148

Descriptive statistics

Standard deviation95.01309046
Coefficient of variation (CV)0.5613927228
Kurtosis-0.8950824038
Mean169.245319
Median Absolute Deviation (MAD)73
Skewness0.2500085563
Sum86403628
Variance9027.487358
MonotonicityNot monotonic
2025-01-07T10:48:07.044182image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140 2508
 
0.4%
141 2480
 
0.4%
134 2427
 
0.4%
135 2416
 
0.4%
150 2398
 
0.4%
136 2383
 
0.4%
142 2380
 
0.4%
166 2363
 
0.4%
139 2354
 
0.4%
132 2338
 
0.4%
Other values (356) 486476
83.2%
(Missing) 74069
 
12.7%
ValueCountFrequency (%)
1 1033
0.2%
2 809
0.1%
3 952
0.2%
4 946
0.2%
5 892
0.2%
ValueCountFrequency (%)
366 148
 
< 0.1%
365 802
0.1%
364 967
0.2%
363 984
0.2%
362 1038
0.2%

year
Real number (ℝ)

Missing 

Distinct204
Distinct (%)< 0.1%
Missing41376
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean1931.530575
Minimum1818
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:07.102931image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1818
5-th percentile1878
Q11904
median1931
Q31960
95-th percentile1989
Maximum2023
Range205
Interquartile range (IQR)56

Descriptive statistics

Standard deviation34.86734233
Coefficient of variation (CV)0.01805166472
Kurtosis-0.638501662
Mean1931.530575
Median Absolute Deviation (MAD)28
Skewness0.1152190339
Sum1049238313
Variance1215.731561
MonotonicityNot monotonic
2025-01-07T10:48:07.162440image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1965 14461
 
2.5%
1964 13001
 
2.2%
1966 10898
 
1.9%
1912 9421
 
1.6%
1911 8196
 
1.4%
1949 8030
 
1.4%
1923 7871
 
1.3%
1950 6975
 
1.2%
1967 6970
 
1.2%
1892 6943
 
1.2%
Other values (194) 450450
77.1%
(Missing) 41376
 
7.1%
ValueCountFrequency (%)
1818 3
 
< 0.1%
1819 3
 
< 0.1%
1820 8
< 0.1%
1821 1
 
< 0.1%
1823 3
 
< 0.1%
ValueCountFrequency (%)
2023 13
 
< 0.1%
2022 21
 
< 0.1%
2021 32
 
< 0.1%
2020 26
 
< 0.1%
2019 146
< 0.1%

month
Real number (ℝ)

Missing 

Distinct12
Distinct (%)< 0.1%
Missing53877
Missing (%)9.2%
Infinite0
Infinite (%)0.0%
Mean6.082102447
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:07.215099image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.119402413
Coefficient of variation (CV)0.5128822542
Kurtosis-0.9144379466
Mean6.082102447
Median Absolute Deviation (MAD)2
Skewness0.2276707259
Sum3227863
Variance9.730671416
MonotonicityNot monotonic
2025-01-07T10:48:07.261611image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5 70341
12.0%
6 61173
10.5%
4 54173
9.3%
3 50525
8.6%
7 46973
8.0%
2 40464
6.9%
8 39913
6.8%
9 37742
6.5%
10 35465
6.1%
1 34467
5.9%
Other values (2) 59479
10.2%
(Missing) 53877
9.2%
ValueCountFrequency (%)
1 34467
5.9%
2 40464
6.9%
3 50525
8.6%
4 54173
9.3%
5 70341
12.0%
ValueCountFrequency (%)
12 28746
4.9%
11 30733
5.3%
10 35465
6.1%
9 37742
6.5%
8 39913
6.8%

day
Real number (ℝ)

Missing 

Distinct31
Distinct (%)< 0.1%
Missing74434
Missing (%)12.7%
Infinite0
Infinite (%)0.0%
Mean15.68671078
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:07.312511image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.711562295
Coefficient of variation (CV)0.5553466508
Kurtosis-1.177162218
Mean15.68671078
Median Absolute Deviation (MAD)7
Skewness0.00422148532
Sum8002701
Variance75.89131762
MonotonicityNot monotonic
2025-01-07T10:48:07.367508image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20 17976
 
3.1%
10 17940
 
3.1%
8 17679
 
3.0%
15 17667
 
3.0%
21 17460
 
3.0%
12 17459
 
3.0%
24 17311
 
3.0%
22 17146
 
2.9%
4 17141
 
2.9%
16 17122
 
2.9%
Other values (21) 335257
57.3%
(Missing) 74434
 
12.7%
ValueCountFrequency (%)
1 16692
2.9%
2 15827
2.7%
3 16750
2.9%
4 17141
2.9%
5 16129
2.8%
ValueCountFrequency (%)
31 8304
1.4%
30 14883
2.5%
29 15184
2.6%
28 16387
2.8%
27 16676
2.9%

verbatimEventDate
Text

Missing 

Distinct43994
Distinct (%)12.6%
Missing235442
Missing (%)40.3%
Memory size4.5 MiB
2025-01-07T10:48:07.552520image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length60
Median length11
Mean length10.64060719
Min length1

Characters and Unicode

Total characters3715168
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10311 ?
Unique (%)3.0%

Sample

1st row-- May 1859
2nd row18 Mar 1883
3rd row26 May 1895
4th row6 Aug 1924
5th row9 Apr 1987
ValueCountFrequency (%)
149965
 
14.3%
may 43235
 
4.1%
jun 37603
 
3.6%
apr 31571
 
3.0%
mar 27292
 
2.6%
jul 27206
 
2.6%
aug 23700
 
2.3%
feb 21866
 
2.1%
sep 21167
 
2.0%
jan 18181
 
1.7%
Other values (727) 644585
61.6%
2025-01-07T10:48:07.814527image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
697221
18.8%
1 503447
13.6%
- 381992
 
10.3%
9 327404
 
8.8%
2 174483
 
4.7%
8 174195
 
4.7%
6 106883
 
2.9%
3 99628
 
2.7%
4 93965
 
2.5%
a 89421
 
2.4%
Other values (67) 1066529
28.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3715168
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
697221
18.8%
1 503447
13.6%
- 381992
 
10.3%
9 327404
 
8.8%
2 174483
 
4.7%
8 174195
 
4.7%
6 106883
 
2.9%
3 99628
 
2.7%
4 93965
 
2.5%
a 89421
 
2.4%
Other values (67) 1066529
28.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3715168
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
697221
18.8%
1 503447
13.6%
- 381992
 
10.3%
9 327404
 
8.8%
2 174483
 
4.7%
8 174195
 
4.7%
6 106883
 
2.9%
3 99628
 
2.7%
4 93965
 
2.5%
a 89421
 
2.4%
Other values (67) 1066529
28.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3715168
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
697221
18.8%
1 503447
13.6%
- 381992
 
10.3%
9 327404
 
8.8%
2 174483
 
4.7%
8 174195
 
4.7%
6 106883
 
2.9%
3 99628
 
2.7%
4 93965
 
2.5%
a 89421
 
2.4%
Other values (67) 1066529
28.7%

habitat
Text

Missing 

Distinct4924
Distinct (%)28.6%
Missing567355
Missing (%)97.1%
Memory size4.5 MiB
2025-01-07T10:48:08.016738image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length191
Median length141
Mean length27.13418808
Min length3

Characters and Unicode

Total characters467712
Distinct characters82
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3478 ?
Unique (%)20.2%

Sample

1st rowIN OPEN OCEAN AT 0835
2nd rowdense marshy grass
3rd rowAlong lake shore, water and dead brush
4th rowairport
5th rowmontane forest edge
ValueCountFrequency (%)
forest 6854
 
9.3%
with 2343
 
3.2%
open 1915
 
2.6%
of 1628
 
2.2%
in 1549
 
2.1%
and 1461
 
2.0%
scrub 1279
 
1.7%
edge 1213
 
1.6%
945
 
1.3%
on 919
 
1.2%
Other values (2526) 53491
72.7%
2025-01-07T10:48:08.289389image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56360
 
12.1%
e 41846
 
8.9%
o 33590
 
7.2%
a 33285
 
7.1%
s 31715
 
6.8%
r 31696
 
6.8%
t 25427
 
5.4%
n 24905
 
5.3%
i 21550
 
4.6%
l 17791
 
3.8%
Other values (72) 149547
32.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 467712
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
56360
 
12.1%
e 41846
 
8.9%
o 33590
 
7.2%
a 33285
 
7.1%
s 31715
 
6.8%
r 31696
 
6.8%
t 25427
 
5.4%
n 24905
 
5.3%
i 21550
 
4.6%
l 17791
 
3.8%
Other values (72) 149547
32.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 467712
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
56360
 
12.1%
e 41846
 
8.9%
o 33590
 
7.2%
a 33285
 
7.1%
s 31715
 
6.8%
r 31696
 
6.8%
t 25427
 
5.4%
n 24905
 
5.3%
i 21550
 
4.6%
l 17791
 
3.8%
Other values (72) 149547
32.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 467712
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
56360
 
12.1%
e 41846
 
8.9%
o 33590
 
7.2%
a 33285
 
7.1%
s 31715
 
6.8%
r 31696
 
6.8%
t 25427
 
5.4%
n 24905
 
5.3%
i 21550
 
4.6%
l 17791
 
3.8%
Other values (72) 149547
32.0%

samplingProtocol
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

sampleSizeValue
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

sampleSizeUnit
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

samplingEffort
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

fieldNotes
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

eventRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

locationID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

higherGeographyID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB
Distinct6798
Distinct (%)1.2%
Missing2
Missing (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:48:08.492737image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length95
Median length75
Mean length36.76763373
Min length4

Characters and Unicode

Total characters21493991
Distinct characters74
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1458 ?
Unique (%)0.2%

Sample

1st rowSouth America, Paraguay, Asuncion
2nd rowNorth America, United States, Florida
3rd rowNorth America, United States, South Dakota
4th rowNorth America, United States, Maine
5th rowAsia, Philippines, Palawan, Palawan Province
ValueCountFrequency (%)
america 389870
 
13.5%
north 349097
 
12.1%
united 213165
 
7.4%
states 211488
 
7.4%
asia 94981
 
3.3%
south 88499
 
3.1%
africa 52986
 
1.8%
mexico 32547
 
1.1%
panama 31800
 
1.1%
colombia 28517
 
1.0%
Other values (4797) 1384325
48.1%
2025-01-07T10:48:08.755396image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2292685
 
10.7%
a 2269264
 
10.6%
i 1576409
 
7.3%
e 1449846
 
6.7%
t 1415514
 
6.6%
r 1302972
 
6.1%
, 1293349
 
6.0%
o 1083406
 
5.0%
n 1034429
 
4.8%
s 708939
 
3.3%
Other values (64) 7067178
32.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21493991
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2292685
 
10.7%
a 2269264
 
10.6%
i 1576409
 
7.3%
e 1449846
 
6.7%
t 1415514
 
6.6%
r 1302972
 
6.1%
, 1293349
 
6.0%
o 1083406
 
5.0%
n 1034429
 
4.8%
s 708939
 
3.3%
Other values (64) 7067178
32.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21493991
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2292685
 
10.7%
a 2269264
 
10.6%
i 1576409
 
7.3%
e 1449846
 
6.7%
t 1415514
 
6.6%
r 1302972
 
6.1%
, 1293349
 
6.0%
o 1083406
 
5.0%
n 1034429
 
4.8%
s 708939
 
3.3%
Other values (64) 7067178
32.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21493991
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2292685
 
10.7%
a 2269264
 
10.6%
i 1576409
 
7.3%
e 1449846
 
6.7%
t 1415514
 
6.6%
r 1302972
 
6.1%
, 1293349
 
6.0%
o 1083406
 
5.0%
n 1034429
 
4.8%
s 708939
 
3.3%
Other values (64) 7067178
32.9%

continent
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing27500
Missing (%)4.7%
Memory size4.5 MiB
2025-01-07T10:48:08.817196image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length10.59729093
Min length4

Characters and Unicode

Total characters5903666
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSOUTH_AMERICA
2nd rowNORTH_AMERICA
3rd rowNORTH_AMERICA
4th rowNORTH_AMERICA
5th rowASIA
ValueCountFrequency (%)
north_america 322157
57.8%
asia 96833
 
17.4%
south_america 69099
 
12.4%
africa 47406
 
8.5%
oceania 11848
 
2.1%
europe 8714
 
1.6%
antarctica 1035
 
0.2%
2025-01-07T10:48:08.999276image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1097791
18.6%
R 770568
13.1%
I 548378
9.3%
C 452580
7.7%
E 420532
 
7.1%
O 411818
 
7.0%
T 393326
 
6.7%
H 391256
 
6.6%
_ 391256
 
6.6%
M 391256
 
6.6%
Other values (5) 634905
10.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5903666
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 1097791
18.6%
R 770568
13.1%
I 548378
9.3%
C 452580
7.7%
E 420532
 
7.1%
O 411818
 
7.0%
T 393326
 
6.7%
H 391256
 
6.6%
_ 391256
 
6.6%
M 391256
 
6.6%
Other values (5) 634905
10.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5903666
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 1097791
18.6%
R 770568
13.1%
I 548378
9.3%
C 452580
7.7%
E 420532
 
7.1%
O 411818
 
7.0%
T 393326
 
6.7%
H 391256
 
6.6%
_ 391256
 
6.6%
M 391256
 
6.6%
Other values (5) 634905
10.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5903666
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 1097791
18.6%
R 770568
13.1%
I 548378
9.3%
C 452580
7.7%
E 420532
 
7.1%
O 411818
 
7.0%
T 393326
 
6.7%
H 391256
 
6.6%
_ 391256
 
6.6%
M 391256
 
6.6%
Other values (5) 634905
10.8%

waterBody
Text

Missing 

Distinct67
Distinct (%)0.3%
Missing558515
Missing (%)95.5%
Memory size4.5 MiB
2025-01-07T10:48:09.068780image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length55
Median length19
Mean length20.14311462
Min length8

Characters and Unicode

Total characters525272
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)0.1%

Sample

1st rowArctic Ocean
2nd rowNorth Pacific Ocean
3rd rowNorth Pacific Ocean
4th rowNorth Pacific Ocean
5th rowNorth Pacific Ocean
ValueCountFrequency (%)
ocean 26055
32.3%
pacific 19043
23.6%
north 16048
19.9%
south 6719
 
8.3%
atlantic 4113
 
5.1%
indian 2690
 
3.3%
sea 2523
 
3.1%
mediterranean 1992
 
2.5%
weddell 131
 
0.2%
arctic 125
 
0.2%
Other values (57) 1126
 
1.4%
2025-01-07T10:48:09.196015image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 68650
13.1%
a 59282
11.3%
54488
10.4%
i 47442
9.0%
n 40099
 
7.6%
e 35322
 
6.7%
t 33362
 
6.4%
O 26120
 
5.0%
o 23090
 
4.4%
h 23023
 
4.4%
Other values (35) 114394
21.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 525272
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 68650
13.1%
a 59282
11.3%
54488
10.4%
i 47442
9.0%
n 40099
 
7.6%
e 35322
 
6.7%
t 33362
 
6.4%
O 26120
 
5.0%
o 23090
 
4.4%
h 23023
 
4.4%
Other values (35) 114394
21.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 525272
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 68650
13.1%
a 59282
11.3%
54488
10.4%
i 47442
9.0%
n 40099
 
7.6%
e 35322
 
6.7%
t 33362
 
6.4%
O 26120
 
5.0%
o 23090
 
4.4%
h 23023
 
4.4%
Other values (35) 114394
21.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 525272
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 68650
13.1%
a 59282
11.3%
54488
10.4%
i 47442
9.0%
n 40099
 
7.6%
e 35322
 
6.7%
t 33362
 
6.4%
O 26120
 
5.0%
o 23090
 
4.4%
h 23023
 
4.4%
Other values (35) 114394
21.8%

islandGroup
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

island
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB
Distinct216
Distinct (%)< 0.1%
Missing3736
Missing (%)0.6%
Memory size4.5 MiB
2025-01-07T10:48:09.376316image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1161712
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st rowPY
2nd rowUS
3rd rowUS
4th rowUS
5th rowPH
ValueCountFrequency (%)
us 216836
37.3%
co 28553
 
4.9%
mx 28229
 
4.9%
pa 27171
 
4.7%
ca 17452
 
3.0%
th 17424
 
3.0%
ph 16446
 
2.8%
zz 16268
 
2.8%
cn 14054
 
2.4%
id 13339
 
2.3%
Other values (206) 185084
31.9%
2025-01-07T10:48:09.604074image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 233998
20.1%
S 224421
19.3%
C 85053
 
7.3%
A 67721
 
5.8%
P 59989
 
5.2%
M 46638
 
4.0%
Z 46463
 
4.0%
T 40681
 
3.5%
E 39938
 
3.4%
H 39416
 
3.4%
Other values (16) 277394
23.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1161712
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 233998
20.1%
S 224421
19.3%
C 85053
 
7.3%
A 67721
 
5.8%
P 59989
 
5.2%
M 46638
 
4.0%
Z 46463
 
4.0%
T 40681
 
3.5%
E 39938
 
3.4%
H 39416
 
3.4%
Other values (16) 277394
23.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1161712
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 233998
20.1%
S 224421
19.3%
C 85053
 
7.3%
A 67721
 
5.8%
P 59989
 
5.2%
M 46638
 
4.0%
Z 46463
 
4.0%
T 40681
 
3.5%
E 39938
 
3.4%
H 39416
 
3.4%
Other values (16) 277394
23.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1161712
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 233998
20.1%
S 224421
19.3%
C 85053
 
7.3%
A 67721
 
5.8%
P 59989
 
5.2%
M 46638
 
4.0%
Z 46463
 
4.0%
T 40681
 
3.5%
E 39938
 
3.4%
H 39416
 
3.4%
Other values (16) 277394
23.9%

stateProvince
Text

Missing 

Distinct2242
Distinct (%)0.5%
Missing93871
Missing (%)16.1%
Memory size4.5 MiB
2025-01-07T10:48:09.787901image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length71
Median length40
Mean length9.131608388
Min length3

Characters and Unicode

Total characters4481072
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique420 ?
Unique (%)0.1%

Sample

1st rowAsuncion
2nd rowFlorida
3rd rowSouth Dakota
4th rowMaine
5th rowPalawan
ValueCountFrequency (%)
california 23409
 
3.6%
new 20454
 
3.1%
alaska 19385
 
3.0%
virginia 14953
 
2.3%
arizona 13147
 
2.0%
maryland 10719
 
1.6%
florida 10644
 
1.6%
texas 9775
 
1.5%
columbia 9291
 
1.4%
island 9097
 
1.4%
Other values (2044) 512747
78.4%
2025-01-07T10:48:10.045254image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 688102
15.4%
i 363250
 
8.1%
n 330347
 
7.4%
o 310192
 
6.9%
r 284632
 
6.4%
e 240206
 
5.4%
l 198665
 
4.4%
s 197499
 
4.4%
162900
 
3.6%
t 158835
 
3.5%
Other values (57) 1546444
34.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4481072
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 688102
15.4%
i 363250
 
8.1%
n 330347
 
7.4%
o 310192
 
6.9%
r 284632
 
6.4%
e 240206
 
5.4%
l 198665
 
4.4%
s 197499
 
4.4%
162900
 
3.6%
t 158835
 
3.5%
Other values (57) 1546444
34.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4481072
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 688102
15.4%
i 363250
 
8.1%
n 330347
 
7.4%
o 310192
 
6.9%
r 284632
 
6.4%
e 240206
 
5.4%
l 198665
 
4.4%
s 197499
 
4.4%
162900
 
3.6%
t 158835
 
3.5%
Other values (57) 1546444
34.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4481072
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 688102
15.4%
i 363250
 
8.1%
n 330347
 
7.4%
o 310192
 
6.9%
r 284632
 
6.4%
e 240206
 
5.4%
l 198665
 
4.4%
s 197499
 
4.4%
162900
 
3.6%
t 158835
 
3.5%
Other values (57) 1546444
34.5%

county
Text

Missing 

Distinct3216
Distinct (%)1.4%
Missing353572
Missing (%)60.5%
Memory size4.5 MiB
2025-01-07T10:48:10.249943image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length39
Median length31
Mean length9.707878106
Min length1

Characters and Unicode

Total characters2242714
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique641 ?
Unique (%)0.3%

Sample

1st rowPalawan Province
2nd rowBergen
3rd rowNorth Solomons Province
4th rowClarke
5th rowAugusta
ValueCountFrequency (%)
area 7116
 
2.1%
census 7108
 
2.1%
province 5993
 
1.8%
bergen 4929
 
1.5%
aleutians 4466
 
1.3%
county 4430
 
1.3%
west 4293
 
1.3%
borough 3777
 
1.1%
san 3628
 
1.1%
latah 3591
 
1.1%
Other values (2933) 289412
85.4%
2025-01-07T10:48:10.522026image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 244424
 
10.9%
e 199313
 
8.9%
n 165552
 
7.4%
o 159648
 
7.1%
r 146489
 
6.5%
i 116092
 
5.2%
107723
 
4.8%
t 103825
 
4.6%
s 98320
 
4.4%
l 98134
 
4.4%
Other values (59) 803194
35.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2242714
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 244424
 
10.9%
e 199313
 
8.9%
n 165552
 
7.4%
o 159648
 
7.1%
r 146489
 
6.5%
i 116092
 
5.2%
107723
 
4.8%
t 103825
 
4.6%
s 98320
 
4.4%
l 98134
 
4.4%
Other values (59) 803194
35.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2242714
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 244424
 
10.9%
e 199313
 
8.9%
n 165552
 
7.4%
o 159648
 
7.1%
r 146489
 
6.5%
i 116092
 
5.2%
107723
 
4.8%
t 103825
 
4.6%
s 98320
 
4.4%
l 98134
 
4.4%
Other values (59) 803194
35.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2242714
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 244424
 
10.9%
e 199313
 
8.9%
n 165552
 
7.4%
o 159648
 
7.1%
r 146489
 
6.5%
i 116092
 
5.2%
107723
 
4.8%
t 103825
 
4.6%
s 98320
 
4.4%
l 98134
 
4.4%
Other values (59) 803194
35.8%

municipality
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

locality
Text

Missing 

Distinct64255
Distinct (%)13.5%
Missing107551
Missing (%)18.4%
Memory size4.5 MiB
2025-01-07T10:48:10.739628image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length929
Median length128
Mean length17.88850853
Min length1

Characters and Unicode

Total characters8533552
Distinct characters112
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33921 ?
Unique (%)7.1%

Sample

1st rowAsuncion
2nd rowBryant, Near
3rd rowOwl'S Head
4th rowNali Barrio, Dam Site, Quezon Municipality
5th rowFort Lee
ValueCountFrequency (%)
island 33520
 
2.4%
mi 31811
 
2.3%
of 23110
 
1.6%
river 22675
 
1.6%
rio 21864
 
1.6%
km 18525
 
1.3%
fort 14257
 
1.0%
san 13196
 
0.9%
near 13030
 
0.9%
lake 11919
 
0.8%
Other values (33466) 1203009
85.5%
2025-01-07T10:48:11.012028image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
929876
 
10.9%
a 913886
 
10.7%
e 542145
 
6.4%
o 539938
 
6.3%
n 524605
 
6.1%
i 502610
 
5.9%
r 415688
 
4.9%
l 354250
 
4.2%
t 336164
 
3.9%
s 280759
 
3.3%
Other values (102) 3193631
37.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8533552
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
929876
 
10.9%
a 913886
 
10.7%
e 542145
 
6.4%
o 539938
 
6.3%
n 524605
 
6.1%
i 502610
 
5.9%
r 415688
 
4.9%
l 354250
 
4.2%
t 336164
 
3.9%
s 280759
 
3.3%
Other values (102) 3193631
37.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8533552
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
929876
 
10.9%
a 913886
 
10.7%
e 542145
 
6.4%
o 539938
 
6.3%
n 524605
 
6.1%
i 502610
 
5.9%
r 415688
 
4.9%
l 354250
 
4.2%
t 336164
 
3.9%
s 280759
 
3.3%
Other values (102) 3193631
37.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8533552
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
929876
 
10.9%
a 913886
 
10.7%
e 542145
 
6.4%
o 539938
 
6.3%
n 524605
 
6.1%
i 502610
 
5.9%
r 415688
 
4.9%
l 354250
 
4.2%
t 336164
 
3.9%
s 280759
 
3.3%
Other values (102) 3193631
37.4%

verbatimLocality
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

verbatimElevation
Text

Missing 

Distinct196
Distinct (%)15.4%
Missing583323
Missing (%)99.8%
Memory size4.5 MiB
2025-01-07T10:48:11.125067image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length84
Median length9
Mean length13.72813239
Min length3

Characters and Unicode

Total characters17421
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)8.5%

Sample

1st rowaltitude uncertain: label says both 5500 ft and 7000 ft
2nd rowca. 1050 m
3rd rowca. 4000 ft
4th rowsea level
5th row6230 ft
ValueCountFrequency (%)
sea 769
20.9%
level 769
20.9%
ft 409
11.1%
ca 177
 
4.8%
m 115
 
3.1%
says 114
 
3.1%
label 100
 
2.7%
altitude 92
 
2.5%
uncertain 74
 
2.0%
of 67
 
1.8%
Other values (170) 986
26.9%
2025-01-07T10:48:11.304977image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2820
16.2%
2403
13.8%
l 1955
11.2%
a 1546
8.9%
0 1357
 
7.8%
s 1076
 
6.2%
t 881
 
5.1%
v 812
 
4.7%
f 520
 
3.0%
n 353
 
2.0%
Other values (45) 3698
21.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17421
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2820
16.2%
2403
13.8%
l 1955
11.2%
a 1546
8.9%
0 1357
 
7.8%
s 1076
 
6.2%
t 881
 
5.1%
v 812
 
4.7%
f 520
 
3.0%
n 353
 
2.0%
Other values (45) 3698
21.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17421
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2820
16.2%
2403
13.8%
l 1955
11.2%
a 1546
8.9%
0 1357
 
7.8%
s 1076
 
6.2%
t 881
 
5.1%
v 812
 
4.7%
f 520
 
3.0%
n 353
 
2.0%
Other values (45) 3698
21.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17421
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2820
16.2%
2403
13.8%
l 1955
11.2%
a 1546
8.9%
0 1357
 
7.8%
s 1076
 
6.2%
t 881
 
5.1%
v 812
 
4.7%
f 520
 
3.0%
n 353
 
2.0%
Other values (45) 3698
21.2%

verticalDatum
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

verbatimDepth
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

minimumDistanceAboveSurfaceInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

maximumDistanceAboveSurfaceInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

locationAccordingTo
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

locationRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

decimalLatitude
Real number (ℝ)

Missing 

Distinct3290
Distinct (%)11.7%
Missing556566
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean14.85522777
Minimum-77.8442
Maximum78.88
Zeros43
Zeros (%)< 0.1%
Negative6085
Negative (%)1.0%
Memory size4.5 MiB
2025-01-07T10:48:11.371485image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-77.8442
5-th percentile-22.38
Q12
median10.08
Q332.67
95-th percentile57.0472
Maximum78.88
Range156.7242
Interquartile range (IQR)30.67

Descriptive statistics

Standard deviation24.35993432
Coefficient of variation (CV)1.639822337
Kurtosis1.004198709
Mean14.85522777
Median Absolute Deviation (MAD)14.08
Skewness-0.2380717987
Sum416332.6134
Variance593.4064001
MonotonicityNot monotonic
2025-01-07T10:48:11.435678image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.9606 991
 
0.2%
31.5011 663
 
0.1%
9.03 591
 
0.1%
8.25 507
 
0.1%
6.45 506
 
0.1%
29.3467 473
 
0.1%
-3.65 448
 
0.1%
-6.17 368
 
0.1%
68.13 307
 
0.1%
-12.63 305
 
0.1%
Other values (3280) 22867
 
3.9%
(Missing) 556566
95.2%
ValueCountFrequency (%)
-77.8442 1
 
< 0.1%
-77.84 1
 
< 0.1%
-77.75 2
< 0.1%
-77.45 3
< 0.1%
-77.15 2
< 0.1%
ValueCountFrequency (%)
78.88 4
< 0.1%
78.73 8
< 0.1%
78.72 1
 
< 0.1%
77 2
 
< 0.1%
76.995 3
 
< 0.1%

decimalLongitude
Real number (ℝ)

Missing 

Distinct3651
Distinct (%)13.0%
Missing556566
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean-27.21473582
Minimum-179.95
Maximum179.52
Zeros1
Zeros (%)< 0.1%
Negative15622
Negative (%)2.7%
Memory size4.5 MiB
2025-01-07T10:48:11.496294image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-179.95
5-th percentile-169.35
Q1-82.27
median-58.2886
Q339.1
95-th percentile116.03
Maximum179.52
Range359.47
Interquartile range (IQR)121.37

Descriptive statistics

Standard deviation89.09830271
Coefficient of variation (CV)-3.273899232
Kurtosis-1.045425919
Mean-27.21473582
Median Absolute Deviation (MAD)91.7314
Skewness0.1116073322
Sum-762720.1862
Variance7938.507545
MonotonicityNot monotonic
2025-01-07T10:48:11.553945image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69.2778 991
 
0.2%
65.8453 663
 
0.1%
36.15 546
 
0.1%
38.18 502
 
0.1%
47.5206 473
 
0.1%
34.58 464
 
0.1%
-52.37 452
 
0.1%
37.5 368
 
0.1%
-165.95 307
 
0.1%
-74.08 295
 
0.1%
Other values (3641) 22965
 
3.9%
(Missing) 556566
95.2%
ValueCountFrequency (%)
-179.95 1
 
< 0.1%
-179.87 1
 
< 0.1%
-179.73 8
< 0.1%
-179.72 1
 
< 0.1%
-179.68 7
< 0.1%
ValueCountFrequency (%)
179.52 1
 
< 0.1%
179.5 1
 
< 0.1%
179.08 3
< 0.1%
179.05 1
 
< 0.1%
179.03 1
 
< 0.1%

coordinateUncertaintyInMeters
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

coordinatePrecision
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

pointRadiusSpatialFit
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB
Distinct4
Distinct (%)< 0.1%
Missing567281
Missing (%)97.0%
Memory size4.5 MiB
2025-01-07T10:48:11.596797image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length22.88076945
Min length3

Characters and Unicode

Total characters396089
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDegrees Minutes Seconds
2nd rowDegrees Minutes Seconds
3rd rowDegrees Minutes Seconds
4th rowDegrees Minutes Seconds
5th rowDegrees Minutes Seconds
ValueCountFrequency (%)
degrees 17208
33.3%
minutes 17206
33.3%
seconds 17206
33.3%
utm 100
 
0.2%
unknown 3
 
< 0.1%
decimal 2
 
< 0.1%
2025-01-07T10:48:11.707127image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 86038
21.7%
s 51620
13.0%
n 34421
 
8.7%
34414
 
8.7%
M 17306
 
4.4%
o 17209
 
4.3%
g 17208
 
4.3%
r 17208
 
4.3%
D 17208
 
4.3%
i 17208
 
4.3%
Other values (12) 86249
21.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 396089
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 86038
21.7%
s 51620
13.0%
n 34421
 
8.7%
34414
 
8.7%
M 17306
 
4.4%
o 17209
 
4.3%
g 17208
 
4.3%
r 17208
 
4.3%
D 17208
 
4.3%
i 17208
 
4.3%
Other values (12) 86249
21.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 396089
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 86038
21.7%
s 51620
13.0%
n 34421
 
8.7%
34414
 
8.7%
M 17306
 
4.4%
o 17209
 
4.3%
g 17208
 
4.3%
r 17208
 
4.3%
D 17208
 
4.3%
i 17208
 
4.3%
Other values (12) 86249
21.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 396089
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 86038
21.7%
s 51620
13.0%
n 34421
 
8.7%
34414
 
8.7%
M 17306
 
4.4%
o 17209
 
4.3%
g 17208
 
4.3%
r 17208
 
4.3%
D 17208
 
4.3%
i 17208
 
4.3%
Other values (12) 86249
21.8%

verbatimSRS
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

footprintWKT
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

footprintSRS
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

footprintSpatialFit
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

georeferencedBy
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

georeferencedDate
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

georeferenceProtocol
Text

Missing 

Distinct11
Distinct (%)0.9%
Missing583342
Missing (%)99.8%
Memory size4.5 MiB
2025-01-07T10:48:11.763131image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length3
Mean length7.1184
Min length3

Characters and Unicode

Total characters8898
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st rowGEOLocate tool
2nd rowGPS
3rd rowGoogle Earth maps
4th rowGPS
5th rowGPS
ValueCountFrequency (%)
gps 739
39.4%
google 195
 
10.4%
earth 195
 
10.4%
maps 195
 
10.4%
geolocate 179
 
9.6%
tool 179
 
9.6%
map 109
 
5.8%
online 18
 
1.0%
not 15
 
0.8%
recorded 15
 
0.8%
Other values (7) 35
 
1.9%
2025-01-07T10:48:11.879963image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 1114
12.5%
o 988
11.1%
P 739
 
8.3%
S 739
 
8.3%
a 700
 
7.9%
624
 
7.0%
t 582
 
6.5%
e 436
 
4.9%
l 413
 
4.6%
E 374
 
4.2%
Other values (23) 2189
24.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8898
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 1114
12.5%
o 988
11.1%
P 739
 
8.3%
S 739
 
8.3%
a 700
 
7.9%
624
 
7.0%
t 582
 
6.5%
e 436
 
4.9%
l 413
 
4.6%
E 374
 
4.2%
Other values (23) 2189
24.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8898
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 1114
12.5%
o 988
11.1%
P 739
 
8.3%
S 739
 
8.3%
a 700
 
7.9%
624
 
7.0%
t 582
 
6.5%
e 436
 
4.9%
l 413
 
4.6%
E 374
 
4.2%
Other values (23) 2189
24.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8898
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 1114
12.5%
o 988
11.1%
P 739
 
8.3%
S 739
 
8.3%
a 700
 
7.9%
624
 
7.0%
t 582
 
6.5%
e 436
 
4.9%
l 413
 
4.6%
E 374
 
4.2%
Other values (23) 2189
24.6%

georeferenceSources
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

georeferenceRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

geologicalContextID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

earliestEonOrLowestEonothem
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

latestEonOrHighestEonothem
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

earliestEraOrLowestErathem
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

latestEraOrHighestErathem
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

earliestPeriodOrLowestSystem
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

latestPeriodOrHighestSystem
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

earliestEpochOrLowestSeries
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

latestEpochOrHighestSeries
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

earliestAgeOrLowestStage
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

latestAgeOrHighestStage
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

lowestBiostratigraphicZone
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

highestBiostratigraphicZone
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

lithostratigraphicTerms
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

group
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

formation
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

member
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

bed
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

identificationID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

verbatimIdentification
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB
Distinct5
Distinct (%)0.7%
Missing583894
Missing (%)99.9%
Memory size4.5 MiB
2025-01-07T10:48:11.929586image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length9
Mean length8.736389685
Min length3

Characters and Unicode

Total characters6098
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowuncertain
2nd rowuncertain
3rd rowuncertain
4th rowuncertain
5th rowuncertain
ValueCountFrequency (%)
uncertain 663
94.3%
cf 29
 
4.1%
sp 4
 
0.6%
aff 4
 
0.6%
near 2
 
0.3%
vel 1
 
0.1%
2025-01-07T10:48:12.024671image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1328
21.8%
c 692
11.3%
a 669
11.0%
e 666
10.9%
r 665
10.9%
u 663
10.9%
t 663
10.9%
i 663
10.9%
f 37
 
0.6%
. 37
 
0.6%
Other values (5) 15
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6098
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1328
21.8%
c 692
11.3%
a 669
11.0%
e 666
10.9%
r 665
10.9%
u 663
10.9%
t 663
10.9%
i 663
10.9%
f 37
 
0.6%
. 37
 
0.6%
Other values (5) 15
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6098
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1328
21.8%
c 692
11.3%
a 669
11.0%
e 666
10.9%
r 665
10.9%
u 663
10.9%
t 663
10.9%
i 663
10.9%
f 37
 
0.6%
. 37
 
0.6%
Other values (5) 15
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6098
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1328
21.8%
c 692
11.3%
a 669
11.0%
e 666
10.9%
r 665
10.9%
u 663
10.9%
t 663
10.9%
i 663
10.9%
f 37
 
0.6%
. 37
 
0.6%
Other values (5) 15
 
0.2%

typeStatus
Text

Missing 

Distinct3
Distinct (%)0.1%
Missing580632
Missing (%)99.3%
Memory size4.5 MiB
2025-01-07T10:48:12.065681image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length4
Mean length4.607323232
Min length4

Characters and Unicode

Total characters18245
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowCOTYPE
2nd rowTYPE
3rd rowTYPE
4th rowTYPE
5th rowTYPE
ValueCountFrequency (%)
type 2759
69.7%
cotype 1200
30.3%
lectotype 1
 
< 0.1%
2025-01-07T10:48:12.157108image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 3961
21.7%
E 3961
21.7%
Y 3960
21.7%
P 3960
21.7%
C 1201
 
6.6%
O 1201
 
6.6%
L 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18245
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
T 3961
21.7%
E 3961
21.7%
Y 3960
21.7%
P 3960
21.7%
C 1201
 
6.6%
O 1201
 
6.6%
L 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18245
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
T 3961
21.7%
E 3961
21.7%
Y 3960
21.7%
P 3960
21.7%
C 1201
 
6.6%
O 1201
 
6.6%
L 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18245
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
T 3961
21.7%
E 3961
21.7%
Y 3960
21.7%
P 3960
21.7%
C 1201
 
6.6%
O 1201
 
6.6%
L 1
 
< 0.1%

identifiedBy
Text

Missing 

Distinct69
Distinct (%)2.0%
Missing581206
Missing (%)99.4%
Memory size4.5 MiB
2025-01-07T10:48:12.279750image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length129
Median length18
Mean length24.97489663
Min length9

Characters and Unicode

Total characters84565
Distinct characters60
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)0.6%

Sample

1st rowWetmore, Alexander
2nd rowMaley, James M, Collections Manager, Occidental College - Moore Laboratory of Zoology (UNITED STATES)
3rd rowWetmore, Alexander
4th rowVerhelst, Juan C
5th rowClark, W. S.
ValueCountFrequency (%)
wetmore 2393
21.9%
alexander 2382
21.8%
of 294
 
2.7%
268
 
2.5%
united 266
 
2.4%
states 265
 
2.4%
museum 246
 
2.3%
natural 200
 
1.8%
history 200
 
1.8%
birds 198
 
1.8%
Other values (178) 4219
38.6%
2025-01-07T10:48:12.548870image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 11582
13.7%
7545
 
8.9%
r 6594
 
7.8%
a 5098
 
6.0%
o 5033
 
6.0%
t 4517
 
5.3%
n 4224
 
5.0%
l 4082
 
4.8%
, 3962
 
4.7%
m 3194
 
3.8%
Other values (50) 28734
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 84565
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 11582
13.7%
7545
 
8.9%
r 6594
 
7.8%
a 5098
 
6.0%
o 5033
 
6.0%
t 4517
 
5.3%
n 4224
 
5.0%
l 4082
 
4.8%
, 3962
 
4.7%
m 3194
 
3.8%
Other values (50) 28734
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 84565
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 11582
13.7%
7545
 
8.9%
r 6594
 
7.8%
a 5098
 
6.0%
o 5033
 
6.0%
t 4517
 
5.3%
n 4224
 
5.0%
l 4082
 
4.8%
, 3962
 
4.7%
m 3194
 
3.8%
Other values (50) 28734
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 84565
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 11582
13.7%
7545
 
8.9%
r 6594
 
7.8%
a 5098
 
6.0%
o 5033
 
6.0%
t 4517
 
5.3%
n 4224
 
5.0%
l 4082
 
4.8%
, 3962
 
4.7%
m 3194
 
3.8%
Other values (50) 28734
34.0%

identifiedByID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

dateIdentified
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

identificationReferences
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

identificationVerificationStatus
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

identificationRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

taxonID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

scientificNameID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

acceptedNameUsageID
Real number (ℝ)

Distinct18485
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5311620.784
Minimum212
Maximum12264592
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:12.623047image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum212
5-th percentile2479449
Q12491482
median6087160
Q37191210
95-th percentile9405036
Maximum12264592
Range12264380
Interquartile range (IQR)4699728

Descriptive statistics

Standard deviation2313117.433
Coefficient of variation (CV)0.4354824125
Kurtosis-0.9233921866
Mean5311620.784
Median Absolute Deviation (MAD)1253908
Skewness0.115057524
Sum3.105131018 × 1012
Variance5.350512261 × 1012
MonotonicityNot monotonic
2025-01-07T10:48:12.689291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9409198 2991
 
0.5%
7192429 1918
 
0.3%
7191991 1808
 
0.3%
9685907 1565
 
0.3%
9791464 1425
 
0.2%
7341805 1363
 
0.2%
2489985 1286
 
0.2%
5231142 1245
 
0.2%
2473421 1244
 
0.2%
2489670 1187
 
0.2%
Other values (18475) 568560
97.3%
ValueCountFrequency (%)
212 12
 
< 0.1%
2877 1
 
< 0.1%
2985 1
 
< 0.1%
2986 55
< 0.1%
5225 107
< 0.1%
ValueCountFrequency (%)
12264592 14
< 0.1%
12234640 6
< 0.1%
12191080 2
 
< 0.1%
12176655 13
< 0.1%
11908959 5
 
< 0.1%

parentNameUsageID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

originalNameUsageID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

nameAccordingToID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

namePublishedInID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

taxonConceptID
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB
Distinct18875
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:12.875171image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length101
Median length68
Mean length36.39443065
Min length4

Characters and Unicode

Total characters21275893
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2553 ?
Unique (%)0.4%

Sample

1st rowParoaria capitata (d'Orbigny & Lafresnaye, 1837)
2nd rowRostrhamus sociabilis (Vieillot, 1817)
3rd rowBartramia longicauda (Bechstein, 1812)
4th rowSterna hirundo Linnaeus, 1758
5th rowPrionochilus plateni W.Blasius, 1888
ValueCountFrequency (%)
linnaeus 95179
 
3.9%
1758 62131
 
2.5%
1766 31804
 
1.3%
1789 23736
 
1.0%
21524
 
0.9%
vieillot 20514
 
0.8%
j.f.gmelin 17875
 
0.7%
ridgway 14989
 
0.6%
dendroica 14825
 
0.6%
gmelin 12921
 
0.5%
Other values (11256) 2141359
87.2%
2025-01-07T10:48:13.154147image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1872265
 
8.8%
a 1760824
 
8.3%
i 1561286
 
7.3%
s 1382114
 
6.5%
e 1247644
 
5.9%
n 1111280
 
5.2%
r 1081068
 
5.1%
u 984426
 
4.6%
l 968653
 
4.6%
o 962179
 
4.5%
Other values (68) 8344154
39.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21275893
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1872265
 
8.8%
a 1760824
 
8.3%
i 1561286
 
7.3%
s 1382114
 
6.5%
e 1247644
 
5.9%
n 1111280
 
5.2%
r 1081068
 
5.1%
u 984426
 
4.6%
l 968653
 
4.6%
o 962179
 
4.5%
Other values (68) 8344154
39.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21275893
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1872265
 
8.8%
a 1760824
 
8.3%
i 1561286
 
7.3%
s 1382114
 
6.5%
e 1247644
 
5.9%
n 1111280
 
5.2%
r 1081068
 
5.1%
u 984426
 
4.6%
l 968653
 
4.6%
o 962179
 
4.5%
Other values (68) 8344154
39.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21275893
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1872265
 
8.8%
a 1760824
 
8.3%
i 1561286
 
7.3%
s 1382114
 
6.5%
e 1247644
 
5.9%
n 1111280
 
5.2%
r 1081068
 
5.1%
u 984426
 
4.6%
l 968653
 
4.6%
o 962179
 
4.5%
Other values (68) 8344154
39.2%

acceptedNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

parentNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

originalNameUsage
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

nameAccordingTo
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

namePublishedIn
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

namePublishedInYear
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB
Distinct185
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:13.351628image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length89
Median length78
Mean length65.97973972
Min length45

Characters and Unicode

Total characters38571228
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowAnimalia, Chordata, Vertebrata, Aves, Passeriformes, Emberizidae, Emberizinae
2nd rowAnimalia, Chordata, Vertebrata, Aves, Falconiformes, Accipitridae
3rd rowAnimalia, Chordata, Vertebrata, Aves, Charadriiformes, Scolopacidae
4th rowAnimalia, Chordata, Vertebrata, Aves, Charadriiformes, Laridae
5th rowAnimalia, Chordata, Vertebrata, Aves, Passeriformes, Dicaeidae
ValueCountFrequency (%)
animalia 584592
16.0%
chordata 584592
16.0%
vertebrata 584592
16.0%
aves 584592
16.0%
passeriformes 372479
10.2%
emberizidae 72754
 
2.0%
emberizinae 50573
 
1.4%
charadriiformes 44080
 
1.2%
parulidae 36362
 
1.0%
tyrannidae 27497
 
0.8%
Other values (206) 702489
19.3%
2025-01-07T10:48:13.611063image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5107701
13.2%
e 3704731
 
9.6%
r 3367631
 
8.7%
3060010
 
7.9%
, 3060009
 
7.9%
i 3035379
 
7.9%
s 1981990
 
5.1%
t 1944511
 
5.0%
o 1467327
 
3.8%
m 1357393
 
3.5%
Other values (37) 10484546
27.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38571228
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5107701
13.2%
e 3704731
 
9.6%
r 3367631
 
8.7%
3060010
 
7.9%
, 3060009
 
7.9%
i 3035379
 
7.9%
s 1981990
 
5.1%
t 1944511
 
5.0%
o 1467327
 
3.8%
m 1357393
 
3.5%
Other values (37) 10484546
27.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38571228
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5107701
13.2%
e 3704731
 
9.6%
r 3367631
 
8.7%
3060010
 
7.9%
, 3060009
 
7.9%
i 3035379
 
7.9%
s 1981990
 
5.1%
t 1944511
 
5.0%
o 1467327
 
3.8%
m 1357393
 
3.5%
Other values (37) 10484546
27.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38571228
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5107701
13.2%
e 3704731
 
9.6%
r 3367631
 
8.7%
3060010
 
7.9%
, 3060009
 
7.9%
i 3035379
 
7.9%
s 1981990
 
5.1%
t 1944511
 
5.0%
o 1467327
 
3.8%
m 1357393
 
3.5%
Other values (37) 10484546
27.2%

kingdom
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:13.665066image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4676736
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowAnimalia
ValueCountFrequency (%)
animalia 584592
100.0%
2025-01-07T10:48:13.761067image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1169184
25.0%
i 1169184
25.0%
n 584592
12.5%
A 584592
12.5%
m 584592
12.5%
l 584592
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4676736
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1169184
25.0%
i 1169184
25.0%
n 584592
12.5%
A 584592
12.5%
m 584592
12.5%
l 584592
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4676736
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1169184
25.0%
i 1169184
25.0%
n 584592
12.5%
A 584592
12.5%
m 584592
12.5%
l 584592
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4676736
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1169184
25.0%
i 1169184
25.0%
n 584592
12.5%
A 584592
12.5%
m 584592
12.5%
l 584592
12.5%

phylum
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:48:13.802639image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4676696
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowChordata
2nd rowChordata
3rd rowChordata
4th rowChordata
5th rowChordata
ValueCountFrequency (%)
chordata 584587
100.0%
2025-01-07T10:48:13.894835image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1169174
25.0%
h 584587
12.5%
C 584587
12.5%
o 584587
12.5%
r 584587
12.5%
d 584587
12.5%
t 584587
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4676696
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1169174
25.0%
h 584587
12.5%
C 584587
12.5%
o 584587
12.5%
r 584587
12.5%
d 584587
12.5%
t 584587
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4676696
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1169174
25.0%
h 584587
12.5%
C 584587
12.5%
o 584587
12.5%
r 584587
12.5%
d 584587
12.5%
t 584587
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4676696
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1169174
25.0%
h 584587
12.5%
C 584587
12.5%
o 584587
12.5%
r 584587
12.5%
d 584587
12.5%
t 584587
12.5%

class
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:48:13.934940image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2338348
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAves
2nd rowAves
3rd rowAves
4th rowAves
5th rowAves
ValueCountFrequency (%)
aves 584587
100.0%
2025-01-07T10:48:14.022761image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 584587
25.0%
v 584587
25.0%
e 584587
25.0%
s 584587
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2338348
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 584587
25.0%
v 584587
25.0%
e 584587
25.0%
s 584587
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2338348
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 584587
25.0%
v 584587
25.0%
e 584587
25.0%
s 584587
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2338348
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 584587
25.0%
v 584587
25.0%
e 584587
25.0%
s 584587
25.0%

order
Text

Distinct42
Distinct (%)< 0.1%
Missing20
Missing (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:48:14.091760image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length13
Mean length12.96889006
Min length10

Characters and Unicode

Total characters7581250
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPasseriformes
2nd rowAccipitriformes
3rd rowCharadriiformes
4th rowCharadriiformes
5th rowPasseriformes
ValueCountFrequency (%)
passeriformes 372474
63.7%
charadriiformes 44387
 
7.6%
piciformes 22599
 
3.9%
apodiformes 18185
 
3.1%
anseriformes 15668
 
2.7%
galliformes 14813
 
2.5%
columbiformes 12800
 
2.2%
accipitriformes 11414
 
2.0%
coraciiformes 7822
 
1.3%
psittaciformes 7419
 
1.3%
Other values (32) 56991
 
9.7%
2025-01-07T10:48:14.218122image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 1353697
17.9%
r 1116871
14.7%
e 999308
13.2%
i 716230
9.4%
o 644987
8.5%
m 602388
7.9%
f 584572
7.7%
a 516843
 
6.8%
P 419526
 
5.5%
c 90235
 
1.2%
Other values (24) 536593
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7581250
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 1353697
17.9%
r 1116871
14.7%
e 999308
13.2%
i 716230
9.4%
o 644987
8.5%
m 602388
7.9%
f 584572
7.7%
a 516843
 
6.8%
P 419526
 
5.5%
c 90235
 
1.2%
Other values (24) 536593
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7581250
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 1353697
17.9%
r 1116871
14.7%
e 999308
13.2%
i 716230
9.4%
o 644987
8.5%
m 602388
7.9%
f 584572
7.7%
a 516843
 
6.8%
P 419526
 
5.5%
c 90235
 
1.2%
Other values (24) 536593
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7581250
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 1353697
17.9%
r 1116871
14.7%
e 999308
13.2%
i 716230
9.4%
o 644987
8.5%
m 602388
7.9%
f 584572
7.7%
a 516843
 
6.8%
P 419526
 
5.5%
c 90235
 
1.2%
Other values (24) 536593
 
7.1%

superfamily
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

family
Text

Distinct239
Distinct (%)< 0.1%
Missing17
Missing (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:48:14.368871image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length16
Mean length10.42056366
Min length7

Characters and Unicode

Total characters6091601
Distinct characters42
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThraupidae
2nd rowAccipitridae
3rd rowScolopacidae
4th rowLaridae
5th rowDicaeidae
ValueCountFrequency (%)
passerellidae 39435
 
6.7%
parulidae 34481
 
5.9%
tyrannidae 26165
 
4.5%
icteridae 19964
 
3.4%
thraupidae 18114
 
3.1%
picidae 17391
 
3.0%
fringillidae 17014
 
2.9%
scolopacidae 16651
 
2.8%
turdidae 16039
 
2.7%
anatidae 15579
 
2.7%
Other values (229) 363742
62.2%
2025-01-07T10:48:14.580091image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 939318
15.4%
i 882003
14.5%
e 764759
12.6%
d 672252
11.0%
r 396820
 
6.5%
l 338348
 
5.6%
c 231479
 
3.8%
o 225694
 
3.7%
n 207894
 
3.4%
t 157040
 
2.6%
Other values (32) 1275994
20.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6091601
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 939318
15.4%
i 882003
14.5%
e 764759
12.6%
d 672252
11.0%
r 396820
 
6.5%
l 338348
 
5.6%
c 231479
 
3.8%
o 225694
 
3.7%
n 207894
 
3.4%
t 157040
 
2.6%
Other values (32) 1275994
20.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6091601
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 939318
15.4%
i 882003
14.5%
e 764759
12.6%
d 672252
11.0%
r 396820
 
6.5%
l 338348
 
5.6%
c 231479
 
3.8%
o 225694
 
3.7%
n 207894
 
3.4%
t 157040
 
2.6%
Other values (32) 1275994
20.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6091601
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 939318
15.4%
i 882003
14.5%
e 764759
12.6%
d 672252
11.0%
r 396820
 
6.5%
l 338348
 
5.6%
c 231479
 
3.8%
o 225694
 
3.7%
n 207894
 
3.4%
t 157040
 
2.6%
Other values (32) 1275994
20.9%

subfamily
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

tribe
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

subtribe
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

genus
Text

Distinct2196
Distinct (%)0.4%
Missing338
Missing (%)0.1%
Memory size4.5 MiB
2025-01-07T10:48:14.779489image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length15
Mean length8.640262626
Min length3

Characters and Unicode

Total characters5048108
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)< 0.1%

Sample

1st rowParoaria
2nd rowRostrhamus
3rd rowBartramia
4th rowSterna
5th rowPrionochilus
ValueCountFrequency (%)
setophaga 18301
 
3.1%
melospiza 7103
 
1.2%
turdus 6838
 
1.2%
calidris 6684
 
1.1%
vireo 6403
 
1.1%
agelaius 5379
 
0.9%
catharus 4885
 
0.8%
junco 4780
 
0.8%
geothlypis 4423
 
0.8%
zonotrichia 4075
 
0.7%
Other values (2186) 515383
88.2%
2025-01-07T10:48:15.048009image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 525335
 
10.4%
o 417081
 
8.3%
i 391104
 
7.7%
s 389715
 
7.7%
r 334572
 
6.6%
e 326852
 
6.5%
u 295820
 
5.9%
l 272317
 
5.4%
t 236060
 
4.7%
n 223789
 
4.4%
Other values (42) 1635463
32.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5048108
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 525335
 
10.4%
o 417081
 
8.3%
i 391104
 
7.7%
s 389715
 
7.7%
r 334572
 
6.6%
e 326852
 
6.5%
u 295820
 
5.9%
l 272317
 
5.4%
t 236060
 
4.7%
n 223789
 
4.4%
Other values (42) 1635463
32.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5048108
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 525335
 
10.4%
o 417081
 
8.3%
i 391104
 
7.7%
s 389715
 
7.7%
r 334572
 
6.6%
e 326852
 
6.5%
u 295820
 
5.9%
l 272317
 
5.4%
t 236060
 
4.7%
n 223789
 
4.4%
Other values (42) 1635463
32.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5048108
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 525335
 
10.4%
o 417081
 
8.3%
i 391104
 
7.7%
s 389715
 
7.7%
r 334572
 
6.6%
e 326852
 
6.5%
u 295820
 
5.9%
l 272317
 
5.4%
t 236060
 
4.7%
n 223789
 
4.4%
Other values (42) 1635463
32.4%
Distinct2024
Distinct (%)0.3%
Missing495
Missing (%)0.1%
Memory size4.5 MiB
2025-01-07T10:48:15.265918image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length15
Mean length8.461623669
Min length3

Characters and Unicode

Total characters4942409
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)< 0.1%

Sample

1st rowParoaria
2nd rowRostrhamus
3rd rowBartramia
4th rowSterna
5th rowPrionochilus
ValueCountFrequency (%)
dendroica 14825
 
2.5%
parus 7485
 
1.3%
melospiza 7103
 
1.2%
turdus 6813
 
1.2%
vireo 6403
 
1.1%
calidris 6372
 
1.1%
sterna 6184
 
1.1%
agelaius 5525
 
0.9%
carduelis 5507
 
0.9%
picoides 5086
 
0.9%
Other values (2014) 512794
87.8%
2025-01-07T10:48:15.541937image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 519400
 
10.5%
i 397930
 
8.1%
o 386413
 
7.8%
s 382857
 
7.7%
r 365575
 
7.4%
u 308704
 
6.2%
e 306794
 
6.2%
l 267331
 
5.4%
n 223958
 
4.5%
c 212647
 
4.3%
Other values (42) 1570800
31.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4942409
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 519400
 
10.5%
i 397930
 
8.1%
o 386413
 
7.8%
s 382857
 
7.7%
r 365575
 
7.4%
u 308704
 
6.2%
e 306794
 
6.2%
l 267331
 
5.4%
n 223958
 
4.5%
c 212647
 
4.3%
Other values (42) 1570800
31.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4942409
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 519400
 
10.5%
i 397930
 
8.1%
o 386413
 
7.8%
s 382857
 
7.7%
r 365575
 
7.4%
u 308704
 
6.2%
e 306794
 
6.2%
l 267331
 
5.4%
n 223958
 
4.5%
c 212647
 
4.3%
Other values (42) 1570800
31.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4942409
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 519400
 
10.5%
i 397930
 
8.1%
o 386413
 
7.8%
s 382857
 
7.7%
r 365575
 
7.4%
u 308704
 
6.2%
e 306794
 
6.2%
l 267331
 
5.4%
n 223958
 
4.5%
c 212647
 
4.3%
Other values (42) 1570800
31.8%

subgenus
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

infragenericEpithet
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

specificEpithet
Text

Missing 

Distinct4643
Distinct (%)0.8%
Missing7917
Missing (%)1.4%
Memory size4.5 MiB
2025-01-07T10:48:15.713459image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length16
Mean length8.786944119
Min length3

Characters and Unicode

Total characters5067211
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique322 ?
Unique (%)0.1%

Sample

1st rowcapitata
2nd rowsociabilis
3rd rowlongicauda
4th rowhirundo
5th rowplateni
ValueCountFrequency (%)
melodia 5111
 
0.9%
phoeniceus 4986
 
0.9%
hyemalis 4880
 
0.8%
americana 4671
 
0.8%
canadensis 3833
 
0.7%
sandwichensis 3774
 
0.7%
pusilla 3572
 
0.6%
alpestris 3345
 
0.6%
olivaceus 3301
 
0.6%
carolinensis 3295
 
0.6%
Other values (4633) 535907
92.9%
2025-01-07T10:48:15.946541image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 623579
12.3%
i 556345
11.0%
s 506337
10.0%
u 361837
 
7.1%
r 360464
 
7.1%
e 352637
 
7.0%
l 331573
 
6.5%
n 305381
 
6.0%
c 304652
 
6.0%
o 272602
 
5.4%
Other values (16) 1091804
21.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5067211
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 623579
12.3%
i 556345
11.0%
s 506337
10.0%
u 361837
 
7.1%
r 360464
 
7.1%
e 352637
 
7.0%
l 331573
 
6.5%
n 305381
 
6.0%
c 304652
 
6.0%
o 272602
 
5.4%
Other values (16) 1091804
21.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5067211
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 623579
12.3%
i 556345
11.0%
s 506337
10.0%
u 361837
 
7.1%
r 360464
 
7.1%
e 352637
 
7.0%
l 331573
 
6.5%
n 305381
 
6.0%
c 304652
 
6.0%
o 272602
 
5.4%
Other values (16) 1091804
21.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5067211
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 623579
12.3%
i 556345
11.0%
s 506337
10.0%
u 361837
 
7.1%
r 360464
 
7.1%
e 352637
 
7.0%
l 331573
 
6.5%
n 305381
 
6.0%
c 304652
 
6.0%
o 272602
 
5.4%
Other values (16) 1091804
21.5%

infraspecificEpithet
Text

Missing 

Distinct6225
Distinct (%)2.3%
Missing308675
Missing (%)52.8%
Memory size4.5 MiB
2025-01-07T10:48:16.104208image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length16
Mean length8.918026073
Min length2

Characters and Unicode

Total characters2460635
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique702 ?
Unique (%)0.3%

Sample

1st rowsolitarius
2nd rowflavoolivaceus
3rd rowsatrapa
4th rowaustralis
5th rowmalherbii
ValueCountFrequency (%)
carolinensis 1803
 
0.7%
olivaceus 1259
 
0.5%
pinus 1235
 
0.4%
occidentalis 1175
 
0.4%
coronata 1165
 
0.4%
pusilla 1144
 
0.4%
flammea 1046
 
0.4%
arizonae 1029
 
0.4%
hyemalis 1005
 
0.4%
frontalis 1004
 
0.4%
Other values (6215) 264052
95.7%
2025-01-07T10:48:16.325753image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 290816
11.8%
a 278989
11.3%
s 254771
10.4%
e 190758
 
7.8%
r 173209
 
7.0%
n 170468
 
6.9%
u 157384
 
6.4%
l 149284
 
6.1%
o 136638
 
5.6%
c 130973
 
5.3%
Other values (17) 527345
21.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2460635
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 290816
11.8%
a 278989
11.3%
s 254771
10.4%
e 190758
 
7.8%
r 173209
 
7.0%
n 170468
 
6.9%
u 157384
 
6.4%
l 149284
 
6.1%
o 136638
 
5.6%
c 130973
 
5.3%
Other values (17) 527345
21.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2460635
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 290816
11.8%
a 278989
11.3%
s 254771
10.4%
e 190758
 
7.8%
r 173209
 
7.0%
n 170468
 
6.9%
u 157384
 
6.4%
l 149284
 
6.1%
o 136638
 
5.6%
c 130973
 
5.3%
Other values (17) 527345
21.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2460635
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 290816
11.8%
a 278989
11.3%
s 254771
10.4%
e 190758
 
7.8%
r 173209
 
7.0%
n 170468
 
6.9%
u 157384
 
6.4%
l 149284
 
6.1%
o 136638
 
5.6%
c 130973
 
5.3%
Other values (17) 527345
21.4%

cultivarEpithet
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:16.385443image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length7
Mean length8.389954019
Min length4

Characters and Unicode

Total characters4904700
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowSPECIES
2nd rowSPECIES
3rd rowSPECIES
4th rowSPECIES
5th rowSPECIES
ValueCountFrequency (%)
species 300916
51.5%
subspecies 275917
47.2%
genus 7422
 
1.3%
family 324
 
0.1%
class 12
 
< 0.1%
form 1
 
< 0.1%
2025-01-07T10:48:16.490185image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 1437029
29.3%
E 1161088
23.7%
I 577157
11.8%
C 576845
11.8%
P 576833
11.8%
U 283339
 
5.8%
B 275917
 
5.6%
G 7422
 
0.2%
N 7422
 
0.2%
A 336
 
< 0.1%
Other values (6) 1312
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4904700
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 1437029
29.3%
E 1161088
23.7%
I 577157
11.8%
C 576845
11.8%
P 576833
11.8%
U 283339
 
5.8%
B 275917
 
5.6%
G 7422
 
0.2%
N 7422
 
0.2%
A 336
 
< 0.1%
Other values (6) 1312
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4904700
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 1437029
29.3%
E 1161088
23.7%
I 577157
11.8%
C 576845
11.8%
P 576833
11.8%
U 283339
 
5.8%
B 275917
 
5.6%
G 7422
 
0.2%
N 7422
 
0.2%
A 336
 
< 0.1%
Other values (6) 1312
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4904700
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 1437029
29.3%
E 1161088
23.7%
I 577157
11.8%
C 576845
11.8%
P 576833
11.8%
U 283339
 
5.8%
B 275917
 
5.6%
G 7422
 
0.2%
N 7422
 
0.2%
A 336
 
< 0.1%
Other values (6) 1312
 
< 0.1%

verbatimTaxonRank
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

vernacularName
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

nomenclaturalCode
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:16.535404image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.793247256
Min length7

Characters and Unicode

Total characters4555870
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowACCEPTED
2nd rowACCEPTED
3rd rowACCEPTED
4th rowACCEPTED
5th rowACCEPTED
ValueCountFrequency (%)
accepted 463081
79.2%
synonym 120866
 
20.7%
doubtful 645
 
0.1%
2025-01-07T10:48:16.715942image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 926162
20.3%
E 926162
20.3%
T 463726
10.2%
D 463726
10.2%
A 463081
10.2%
P 463081
10.2%
Y 241732
 
5.3%
N 241732
 
5.3%
O 121511
 
2.7%
S 120866
 
2.7%
Other values (5) 124091
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4555870
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 926162
20.3%
E 926162
20.3%
T 463726
10.2%
D 463726
10.2%
A 463081
10.2%
P 463081
10.2%
Y 241732
 
5.3%
N 241732
 
5.3%
O 121511
 
2.7%
S 120866
 
2.7%
Other values (5) 124091
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4555870
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 926162
20.3%
E 926162
20.3%
T 463726
10.2%
D 463726
10.2%
A 463081
10.2%
P 463081
10.2%
Y 241732
 
5.3%
N 241732
 
5.3%
O 121511
 
2.7%
S 120866
 
2.7%
Other values (5) 124091
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4555870
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 926162
20.3%
E 926162
20.3%
T 463726
10.2%
D 463726
10.2%
A 463081
10.2%
P 463081
10.2%
Y 241732
 
5.3%
N 241732
 
5.3%
O 121511
 
2.7%
S 120866
 
2.7%
Other values (5) 124091
 
2.7%

nomenclaturalStatus
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

taxonRemarks
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

datasetKey
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:16.768940image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters21045312
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row821cc27a-e3bb-4bc5-ac34-89ada245069d
2nd row821cc27a-e3bb-4bc5-ac34-89ada245069d
3rd row821cc27a-e3bb-4bc5-ac34-89ada245069d
4th row821cc27a-e3bb-4bc5-ac34-89ada245069d
5th row821cc27a-e3bb-4bc5-ac34-89ada245069d
ValueCountFrequency (%)
821cc27a-e3bb-4bc5-ac34-89ada245069d 584592
100.0%
2025-01-07T10:48:16.869254image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 2338368
11.1%
a 2338368
11.1%
- 2338368
11.1%
2 1753776
8.3%
4 1753776
8.3%
b 1753776
8.3%
8 1169184
 
5.6%
3 1169184
 
5.6%
9 1169184
 
5.6%
d 1169184
 
5.6%
Other values (6) 4092144
19.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21045312
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 2338368
11.1%
a 2338368
11.1%
- 2338368
11.1%
2 1753776
8.3%
4 1753776
8.3%
b 1753776
8.3%
8 1169184
 
5.6%
3 1169184
 
5.6%
9 1169184
 
5.6%
d 1169184
 
5.6%
Other values (6) 4092144
19.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21045312
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 2338368
11.1%
a 2338368
11.1%
- 2338368
11.1%
2 1753776
8.3%
4 1753776
8.3%
b 1753776
8.3%
8 1169184
 
5.6%
3 1169184
 
5.6%
9 1169184
 
5.6%
d 1169184
 
5.6%
Other values (6) 4092144
19.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21045312
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 2338368
11.1%
a 2338368
11.1%
- 2338368
11.1%
2 1753776
8.3%
4 1753776
8.3%
b 1753776
8.3%
8 1169184
 
5.6%
3 1169184
 
5.6%
9 1169184
 
5.6%
d 1169184
 
5.6%
Other values (6) 4092144
19.4%

publishingCountry
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:16.909266image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1169184
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUS
2nd rowUS
3rd rowUS
4th rowUS
5th rowUS
ValueCountFrequency (%)
us 584592
100.0%
2025-01-07T10:48:16.999607image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 584592
50.0%
S 584592
50.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1169184
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 584592
50.0%
S 584592
50.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1169184
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 584592
50.0%
S 584592
50.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1169184
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 584592
50.0%
S 584592
50.0%
Distinct183965
Distinct (%)31.5%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:17.142825image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99608616
Min length20

Characters and Unicode

Total characters14027920
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40346 ?
Unique (%)6.9%

Sample

1st row2024-12-02T13:56:05.137Z
2nd row2024-12-02T13:56:08.067Z
3rd row2024-12-02T13:59:48.585Z
4th row2024-12-02T13:56:09.311Z
5th row2024-12-02T13:58:24.805Z
ValueCountFrequency (%)
2024-12-02t13:57:59.341z 17
 
< 0.1%
2024-12-02t13:57:53.841z 16
 
< 0.1%
2024-12-02t13:57:38.028z 16
 
< 0.1%
2024-12-02t13:57:45.007z 16
 
< 0.1%
2024-12-02t13:57:44.964z 15
 
< 0.1%
2024-12-02t13:58:02.554z 15
 
< 0.1%
2024-12-02t13:57:00.688z 15
 
< 0.1%
2024-12-02t13:57:00.663z 15
 
< 0.1%
2024-12-02t13:58:00.792z 15
 
< 0.1%
2024-12-02t13:57:41.116z 15
 
< 0.1%
Other values (183955) 584437
> 99.9%
2025-01-07T10:48:17.366308image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2670609
19.0%
0 1482175
10.6%
1 1475322
10.5%
- 1169184
8.3%
: 1169184
8.3%
4 940152
 
6.7%
5 927783
 
6.6%
3 925430
 
6.6%
T 584592
 
4.2%
Z 584592
 
4.2%
Other values (5) 2098897
15.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14027920
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2670609
19.0%
0 1482175
10.6%
1 1475322
10.5%
- 1169184
8.3%
: 1169184
8.3%
4 940152
 
6.7%
5 927783
 
6.6%
3 925430
 
6.6%
T 584592
 
4.2%
Z 584592
 
4.2%
Other values (5) 2098897
15.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14027920
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2670609
19.0%
0 1482175
10.6%
1 1475322
10.5%
- 1169184
8.3%
: 1169184
8.3%
4 940152
 
6.7%
5 927783
 
6.6%
3 925430
 
6.6%
T 584592
 
4.2%
Z 584592
 
4.2%
Other values (5) 2098897
15.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14027920
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2670609
19.0%
0 1482175
10.6%
1 1475322
10.5%
- 1169184
8.3%
: 1169184
8.3%
4 940152
 
6.7%
5 927783
 
6.6%
3 925430
 
6.6%
T 584592
 
4.2%
Z 584592
 
4.2%
Other values (5) 2098897
15.0%

elevation
Real number (ℝ)

Missing 

Distinct1379
Distinct (%)1.6%
Missing498000
Missing (%)85.2%
Infinite0
Infinite (%)0.0%
Mean1246.618211
Minimum-81
Maximum9500
Zeros826
Zeros (%)0.1%
Negative2
Negative (%)< 0.1%
Memory size4.5 MiB
2025-01-07T10:48:17.440277image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-81
5-th percentile50
Q1411.5
median1128
Q31829
95-th percentile3048
Maximum9500
Range9581
Interquartile range (IQR)1417.5

Descriptive statistics

Standard deviation970.0438514
Coefficient of variation (CV)0.7781402863
Kurtosis0.5443030843
Mean1246.618211
Median Absolute Deviation (MAD)701
Skewness0.8513860493
Sum107947164.1
Variance940985.0736
MonotonicityNot monotonic
2025-01-07T10:48:17.501278image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1829 2382
 
0.4%
914 2016
 
0.3%
1219 1941
 
0.3%
610 1879
 
0.3%
1524 1853
 
0.3%
1676 1775
 
0.3%
2134 1668
 
0.3%
305 1650
 
0.3%
1067 1237
 
0.2%
1372 1235
 
0.2%
Other values (1369) 68956
 
11.8%
(Missing) 498000
85.2%
ValueCountFrequency (%)
-81 1
 
< 0.1%
-61 1
 
< 0.1%
0 826
0.1%
0.5 8
 
< 0.1%
1 14
 
< 0.1%
ValueCountFrequency (%)
9500 1
< 0.1%
8000 1
< 0.1%
7925 1
< 0.1%
7600 1
< 0.1%
5395 1
< 0.1%

elevationAccuracy
Real number (ℝ)

Missing 

Distinct89
Distinct (%)0.9%
Missing574752
Missing (%)98.3%
Infinite0
Infinite (%)0.0%
Mean104.401626
Minimum0
Maximum914.5
Zeros394
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:17.562412image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.5
Q161
median76.5
Q3152.5
95-th percentile228.5
Maximum914.5
Range914.5
Interquartile range (IQR)91.5

Descriptive statistics

Standard deviation72.3507132
Coefficient of variation (CV)0.6930037009
Kurtosis5.966424251
Mean104.401626
Median Absolute Deviation (MAD)46
Skewness1.623369333
Sum1027312
Variance5234.625701
MonotonicityNot monotonic
2025-01-07T10:48:17.623389image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
152.5 2223
 
0.4%
76 1274
 
0.2%
76.5 1047
 
0.2%
30.5 536
 
0.1%
45.5 426
 
0.1%
61 404
 
0.1%
0 394
 
0.1%
106.5 310
 
0.1%
91.5 290
 
< 0.1%
46 265
 
< 0.1%
Other values (79) 2671
 
0.5%
(Missing) 574752
98.3%
ValueCountFrequency (%)
0 394
0.1%
3 3
 
< 0.1%
4 3
 
< 0.1%
7.5 13
 
< 0.1%
8.5 2
 
< 0.1%
ValueCountFrequency (%)
914.5 1
 
< 0.1%
762 1
 
< 0.1%
609.5 1
 
< 0.1%
457.5 36
< 0.1%
457 1
 
< 0.1%

depth
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

depthAccuracy
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

distanceFromCentroidInMeters
Real number (ℝ)

Missing 

Distinct5
Distinct (%)62.5%
Missing584584
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean2967.425413
Minimum368.7454186
Maximum4411.160071
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:17.672391image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum368.7454186
5-th percentile561.0320544
Q12040.032555
median3402.521864
Q34411.160071
95-th percentile4411.160071
Maximum4411.160071
Range4042.414653
Interquartile range (IQR)2371.127516

Descriptive statistics

Standard deviation1683.749761
Coefficient of variation (CV)0.5674109797
Kurtosis-1.463011888
Mean2967.425413
Median Absolute Deviation (MAD)1008.638208
Skewness-0.5818430238
Sum23739.4033
Variance2835013.257
MonotonicityNot monotonic
2025-01-07T10:48:17.721695image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
4411.160071 3
 
< 0.1%
2413.998138 2
 
< 0.1%
368.7454186 1
 
< 0.1%
918.1358065 1
 
< 0.1%
4391.045589 1
 
< 0.1%
(Missing) 584584
> 99.9%
ValueCountFrequency (%)
368.7454186 1
 
< 0.1%
918.1358065 1
 
< 0.1%
2413.998138 2
< 0.1%
4391.045589 1
 
< 0.1%
4411.160071 3
< 0.1%
ValueCountFrequency (%)
4411.160071 3
< 0.1%
4391.045589 1
 
< 0.1%
2413.998138 2
< 0.1%
918.1358065 1
 
< 0.1%
368.7454186 1
 
< 0.1%

issue
Text

Distinct74
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:17.774694image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length186
Median length48
Mean length53.02144744
Min length48

Characters and Unicode

Total characters30995914
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)< 0.1%

Sample

1st rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
2nd rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
3rd rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
4th rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
5th rowOCCURRENCE_STATUS_INFERRED_FROM_INDIVIDUAL_COUNT
ValueCountFrequency (%)
occurrence_status_inferred_from_individual_count 488030
83.5%
occurrence_status_inferred_from_individual_count;taxon_match_higherrank 40818
 
7.0%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84 19491
 
3.3%
occurrence_status_inferred_from_individual_count;taxon_match_fuzzy 14228
 
2.4%
occurrence_status_inferred_from_individual_count;continent_derived_from_country;continent_invalid 10628
 
1.8%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;taxon_match_higherrank 2362
 
0.4%
occurrence_status_inferred_from_individual_count;country_derived_from_coordinates;geodetic_datum_assumed_wgs84;continent_invalid 2250
 
0.4%
occurrence_status_inferred_from_individual_count;geodetic_datum_assumed_wgs84;continent_invalid 1482
 
0.3%
occurrence_status_inferred_from_individual_count;continent_derived_from_country;continent_invalid;taxon_match_higherrank 777
 
0.1%
occurrence_status_inferred_from_individual_count;continent_country_mismatch 752
 
0.1%
Other values (64) 3774
 
0.6%
2025-01-07T10:48:17.907774image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 3192048
10.3%
R 3060927
9.9%
N 2568512
 
8.3%
E 2532321
 
8.2%
I 2495611
 
8.1%
C 2478423
 
8.0%
U 2425637
 
7.8%
T 2012103
 
6.5%
O 1910196
 
6.2%
D 1890173
 
6.1%
Other values (17) 6429963
20.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 30995914
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
_ 3192048
10.3%
R 3060927
9.9%
N 2568512
 
8.3%
E 2532321
 
8.2%
I 2495611
 
8.1%
C 2478423
 
8.0%
U 2425637
 
7.8%
T 2012103
 
6.5%
O 1910196
 
6.2%
D 1890173
 
6.1%
Other values (17) 6429963
20.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 30995914
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
_ 3192048
10.3%
R 3060927
9.9%
N 2568512
 
8.3%
E 2532321
 
8.2%
I 2495611
 
8.1%
C 2478423
 
8.0%
U 2425637
 
7.8%
T 2012103
 
6.5%
O 1910196
 
6.2%
D 1890173
 
6.1%
Other values (17) 6429963
20.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 30995914
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
_ 3192048
10.3%
R 3060927
9.9%
N 2568512
 
8.3%
E 2532321
 
8.2%
I 2495611
 
8.1%
C 2478423
 
8.0%
U 2425637
 
7.8%
T 2012103
 
6.5%
O 1910196
 
6.2%
D 1890173
 
6.1%
Other values (17) 6429963
20.7%

mediaType
Text

Missing 

Distinct65
Distinct (%)< 0.1%
Missing26095
Missing (%)4.5%
Memory size4.5 MiB
2025-01-07T10:48:17.962288image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1165
Median length10
Mean length10.99926231
Min length10

Characters and Unicode

Total characters6143055
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)< 0.1%

Sample

1st rowStillImage
2nd rowStillImage
3rd rowStillImage
4th rowStillImage
5th rowStillImage
ValueCountFrequency (%)
stillimage 544064
97.4%
stillimage;stillimage 6302
 
1.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 4028
 
0.7%
stillimage;stillimage;stillimage;stillimage 1341
 
0.2%
stillimage;stillimage;stillimage 1085
 
0.2%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 446
 
0.1%
stillimage;stillimage;stillimage;stillimage;stillimage 299
 
0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 160
 
< 0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 119
 
< 0.1%
stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage;stillimage 99
 
< 0.1%
Other values (55) 554
 
0.1%
2025-01-07T10:48:18.089153image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1218464
19.8%
S 609232
9.9%
t 609232
9.9%
i 609232
9.9%
I 609232
9.9%
m 609232
9.9%
a 609232
9.9%
g 609232
9.9%
e 609232
9.9%
; 50735
 
0.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6143055
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 1218464
19.8%
S 609232
9.9%
t 609232
9.9%
i 609232
9.9%
I 609232
9.9%
m 609232
9.9%
a 609232
9.9%
g 609232
9.9%
e 609232
9.9%
; 50735
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6143055
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 1218464
19.8%
S 609232
9.9%
t 609232
9.9%
i 609232
9.9%
I 609232
9.9%
m 609232
9.9%
a 609232
9.9%
g 609232
9.9%
e 609232
9.9%
; 50735
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6143055
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 1218464
19.8%
S 609232
9.9%
t 609232
9.9%
i 609232
9.9%
I 609232
9.9%
m 609232
9.9%
a 609232
9.9%
g 609232
9.9%
e 609232
9.9%
; 50735
 
0.8%

hasCoordinate
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size571.0 KiB
False
556566 
True
 
28026
ValueCountFrequency (%)
False 556566
95.2%
True 28026
 
4.8%
2025-01-07T10:48:18.143659image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

hasGeospatialIssues
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size571.0 KiB
False
584063 
True
 
529
ValueCountFrequency (%)
False 584063
99.9%
True 529
 
0.1%
2025-01-07T10:48:18.182770image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

taxonKey
Real number (ℝ)

Distinct18875
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5002380.094
Minimum212
Maximum12386324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:18.237280image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum212
5-th percentile2479418
Q12489988
median5231705.5
Q36176491
95-th percentile9124950
Maximum12386324
Range12386112
Interquartile range (IQR)3686503

Descriptive statistics

Standard deviation2188531.518
Coefficient of variation (CV)0.4374980464
Kurtosis-0.8541846375
Mean5002380.094
Median Absolute Deviation (MAD)1960626.5
Skewness0.2063823943
Sum2.924351384 × 1012
Variance4.789670207 × 1012
MonotonicityNot monotonic
2025-01-07T10:48:18.301798image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9409198 2991
 
0.5%
5229252 1915
 
0.3%
9685907 1565
 
0.3%
9791464 1425
 
0.2%
2489985 1281
 
0.2%
5231142 1245
 
0.2%
2473421 1244
 
0.2%
2489670 1187
 
0.2%
7191634 1155
 
0.2%
2489730 1077
 
0.2%
Other values (18865) 569507
97.4%
ValueCountFrequency (%)
212 12
 
< 0.1%
2877 1
 
< 0.1%
2985 1
 
< 0.1%
2986 55
< 0.1%
5225 107
< 0.1%
ValueCountFrequency (%)
12386324 6
< 0.1%
12264592 14
< 0.1%
12234640 6
< 0.1%
12191080 2
 
< 0.1%
12176655 13
< 0.1%

acceptedTaxonKey
Real number (ℝ)

Distinct18485
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5311620.784
Minimum212
Maximum12264592
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:18.367302image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum212
5-th percentile2479449
Q12491482
median6087160
Q37191210
95-th percentile9405036
Maximum12264592
Range12264380
Interquartile range (IQR)4699728

Descriptive statistics

Standard deviation2313117.433
Coefficient of variation (CV)0.4354824125
Kurtosis-0.9233921866
Mean5311620.784
Median Absolute Deviation (MAD)1253908
Skewness0.115057524
Sum3.105131018 × 1012
Variance5.350512261 × 1012
MonotonicityNot monotonic
2025-01-07T10:48:18.433537image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9409198 2991
 
0.5%
7192429 1918
 
0.3%
7191991 1808
 
0.3%
9685907 1565
 
0.3%
9791464 1425
 
0.2%
7341805 1363
 
0.2%
2489985 1286
 
0.2%
5231142 1245
 
0.2%
2473421 1244
 
0.2%
2489670 1187
 
0.2%
Other values (18475) 568560
97.3%
ValueCountFrequency (%)
212 12
 
< 0.1%
2877 1
 
< 0.1%
2985 1
 
< 0.1%
2986 55
< 0.1%
5225 107
< 0.1%
ValueCountFrequency (%)
12264592 14
< 0.1%
12234640 6
< 0.1%
12191080 2
 
< 0.1%
12176655 13
< 0.1%
11908959 5
 
< 0.1%

kingdomKey
Real number (ℝ)

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:18.484460image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum584592
Variance0
MonotonicityIncreasing
2025-01-07T10:48:18.527216image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1 584592
100.0%
ValueCountFrequency (%)
1 584592
100.0%
ValueCountFrequency (%)
1 584592
100.0%

phylumKey
Real number (ℝ)

Constant 

Distinct1
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean44
Minimum44
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:18.568216image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile44
Q144
median44
Q344
95-th percentile44
Maximum44
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean44
Median Absolute Deviation (MAD)0
Skewness0
Sum25721828
Variance0
MonotonicityIncreasing
2025-01-07T10:48:18.705527image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
44 584587
> 99.9%
(Missing) 5
 
< 0.1%
ValueCountFrequency (%)
44 584587
> 99.9%
ValueCountFrequency (%)
44 584587
> 99.9%

classKey
Real number (ℝ)

Constant 

Distinct1
Distinct (%)< 0.1%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean212
Minimum212
Maximum212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:18.747098image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum212
5-th percentile212
Q1212
median212
Q3212
95-th percentile212
Maximum212
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean212
Median Absolute Deviation (MAD)0
Skewness0
Sum123932444
Variance0
MonotonicityIncreasing
2025-01-07T10:48:18.790637image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
212 584587
> 99.9%
(Missing) 5
 
< 0.1%
ValueCountFrequency (%)
212 584587
> 99.9%
ValueCountFrequency (%)
212 584587
> 99.9%

orderKey
Real number (ℝ)

Distinct42
Distinct (%)< 0.1%
Missing20
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1081671.149
Minimum716
Maximum10833565
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:18.844151image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum716
5-th percentile724
Q1729
median729
Q31446
95-th percentile7192402
Maximum10833565
Range10832849
Interquartile range (IQR)717

Descriptive statistics

Standard deviation2587970.658
Coefficient of variation (CV)2.392566965
Kurtosis1.964638566
Mean1081671.149
Median Absolute Deviation (MAD)0
Skewness1.984496649
Sum6.323146667 × 1011
Variance6.697592125 × 1012
MonotonicityNot monotonic
2025-01-07T10:48:18.902676image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
729 372474
63.7%
7192402 44387
 
7.6%
724 22599
 
3.9%
1448 18185
 
3.1%
1108 15668
 
2.7%
723 14813
 
2.5%
1446 12800
 
2.2%
7191147 11414
 
2.0%
1447 7822
 
1.3%
1445 7419
 
1.3%
Other values (32) 56991
 
9.7%
ValueCountFrequency (%)
716 1625
 
0.3%
721 414
 
0.1%
723 14813
2.5%
724 22599
3.9%
725 79
 
< 0.1%
ValueCountFrequency (%)
10833565 87
< 0.1%
10726067 24
 
< 0.1%
8708973 183
< 0.1%
8706725 28
 
< 0.1%
8705315 54
 
< 0.1%

familyKey
Real number (ℝ)

Distinct239
Distinct (%)< 0.1%
Missing17
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean924800.5755
Minimum2877
Maximum9619755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:18.963187image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2877
5-th percentile2986
Q15263
median6176
Q39340
95-th percentile9410667
Maximum9619755
Range9616878
Interquartile range (IQR)4077

Descriptive statistics

Standard deviation2581901.814
Coefficient of variation (CV)2.79184711
Kurtosis5.569424398
Mean924800.5755
Median Absolute Deviation (MAD)3117
Skewness2.675224525
Sum5.406152964 × 1011
Variance6.666216978 × 1012
MonotonicityNot monotonic
2025-01-07T10:48:19.028311image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9410667 39435
 
6.7%
5263 34481
 
5.9%
5291 26165
 
4.5%
6176 19964
 
3.4%
9352 18114
 
3.1%
9333 17391
 
3.0%
5242 17014
 
2.9%
5282 16651
 
2.8%
5290 16039
 
2.7%
2986 15579
 
2.7%
Other values (229) 363742
62.2%
ValueCountFrequency (%)
2877 10161
1.7%
2878 1017
 
0.2%
2879 429
 
0.1%
2984 4456
0.8%
2985 4166
0.7%
ValueCountFrequency (%)
9619755 65
 
< 0.1%
9509077 13
 
< 0.1%
9410667 39435
6.7%
9402236 85
 
< 0.1%
9397627 105
 
< 0.1%

genusKey
Real number (ℝ)

Distinct2196
Distinct (%)0.4%
Missing338
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean3092499.869
Minimum1686160
Maximum11301485
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:19.093112image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1686160
5-th percentile2476058
Q12482766
median2489984
Q32494085
95-th percentile7341726
Maximum11301485
Range9615325
Interquartile range (IQR)11319

Descriptive statistics

Standard deviation1620486.579
Coefficient of variation (CV)0.5240053833
Kurtosis7.208322901
Mean3092499.869
Median Absolute Deviation (MAD)6224
Skewness2.807224218
Sum1.806805418 × 1012
Variance2.625976753 × 1012
MonotonicityNot monotonic
2025-01-07T10:48:19.154624image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2489984 18301
 
3.1%
2492191 7103
 
1.2%
2490714 6838
 
1.2%
2481739 6684
 
1.1%
2487406 6403
 
1.1%
2484444 5379
 
0.9%
2490799 4885
 
0.8%
2492009 4780
 
0.8%
2489637 4423
 
0.8%
6173226 4075
 
0.7%
Other values (2186) 515383
88.2%
ValueCountFrequency (%)
1686160 201
 
< 0.1%
2235048 532
0.1%
2336662 507
0.1%
2473324 30
 
< 0.1%
2473335 15
 
< 0.1%
ValueCountFrequency (%)
11301485 26
 
< 0.1%
11072875 6
 
< 0.1%
11048324 20
 
< 0.1%
11016979 2486
0.4%
10831800 3
 
< 0.1%

subgenusKey
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

speciesKey
Real number (ℝ)

Missing 

Distinct8234
Distinct (%)1.4%
Missing7853
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean4205581.718
Minimum2473325
Maximum11705322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:19.214801image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2473325
5-th percentile2477282
Q12484609
median2492996
Q35231685
95-th percentile9510564
Maximum11705322
Range9231997
Interquartile range (IQR)2747076

Descriptive statistics

Standard deviation2459105.239
Coefficient of variation (CV)0.5847241603
Kurtosis-0.01425315475
Mean4205581.718
Median Absolute Deviation (MAD)12091
Skewness1.144467627
Sum2.425522995 × 1012
Variance6.047198575 × 1012
MonotonicityNot monotonic
2025-01-07T10:48:19.277801image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2492196 5111
 
0.9%
9409198 4956
 
0.8%
9362842 4264
 
0.7%
5231142 3641
 
0.6%
9415596 3345
 
0.6%
2489670 2973
 
0.5%
9510564 2633
 
0.5%
5789284 1921
 
0.3%
5231132 1886
 
0.3%
2478259 1885
 
0.3%
Other values (8224) 544124
93.1%
(Missing) 7853
 
1.3%
ValueCountFrequency (%)
2473325 24
< 0.1%
2473332 6
 
< 0.1%
2473336 14
< 0.1%
2473337 1
 
< 0.1%
2473339 26
< 0.1%
ValueCountFrequency (%)
11705322 1
 
< 0.1%
11641412 1
 
< 0.1%
11366957 108
< 0.1%
11345373 64
< 0.1%
11336252 2
 
< 0.1%

species
Text

Missing 

Distinct8234
Distinct (%)1.4%
Missing7853
Missing (%)1.3%
Memory size4.5 MiB
2025-01-07T10:48:19.434885image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length29
Mean length18.43415132
Min length9

Characters and Unicode

Total characters10631694
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique681 ?
Unique (%)0.1%

Sample

1st rowParoaria capitata
2nd rowRostrhamus sociabilis
3rd rowBartramia longicauda
4th rowSterna hirundo
5th rowPrionochilus plateni
ValueCountFrequency (%)
setophaga 18263
 
1.6%
melospiza 7103
 
0.6%
turdus 6787
 
0.6%
calidris 6682
 
0.6%
vireo 6370
 
0.6%
agelaius 5367
 
0.5%
melodia 5111
 
0.4%
phoeniceus 4986
 
0.4%
catharus 4865
 
0.4%
hyemalis 4856
 
0.4%
Other values (6762) 1083406
93.9%
2025-01-07T10:48:19.667077image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1140380
 
10.7%
i 948191
 
8.9%
s 897805
 
8.4%
r 687139
 
6.5%
o 682086
 
6.4%
e 675341
 
6.4%
u 655256
 
6.2%
l 598920
 
5.6%
577057
 
5.4%
n 529238
 
5.0%
Other values (43) 3240281
30.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10631694
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1140380
 
10.7%
i 948191
 
8.9%
s 897805
 
8.4%
r 687139
 
6.5%
o 682086
 
6.4%
e 675341
 
6.4%
u 655256
 
6.2%
l 598920
 
5.6%
577057
 
5.4%
n 529238
 
5.0%
Other values (43) 3240281
30.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10631694
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1140380
 
10.7%
i 948191
 
8.9%
s 897805
 
8.4%
r 687139
 
6.5%
o 682086
 
6.4%
e 675341
 
6.4%
u 655256
 
6.2%
l 598920
 
5.6%
577057
 
5.4%
n 529238
 
5.0%
Other values (43) 3240281
30.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10631694
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1140380
 
10.7%
i 948191
 
8.9%
s 897805
 
8.4%
r 687139
 
6.5%
o 682086
 
6.4%
e 675341
 
6.4%
u 655256
 
6.2%
l 598920
 
5.6%
577057
 
5.4%
n 529238
 
5.0%
Other values (43) 3240281
30.5%
Distinct18485
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:19.880410image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length101
Median length69
Mean length36.3684775
Min length4

Characters and Unicode

Total characters21260721
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2480 ?
Unique (%)0.4%

Sample

1st rowParoaria capitata (d'Orbigny & Lafresnaye, 1837)
2nd rowRostrhamus sociabilis (Vieillot, 1817)
3rd rowBartramia longicauda (Bechstein, 1812)
4th rowSterna hirundo Linnaeus, 1758
5th rowPrionochilus plateni W.Blasius, 1888
ValueCountFrequency (%)
linnaeus 96059
 
3.9%
1758 62975
 
2.6%
1766 31923
 
1.3%
1789 22527
 
0.9%
21216
 
0.9%
vieillot 20464
 
0.8%
setophaga 18301
 
0.8%
j.f.gmelin 17514
 
0.7%
ridgway 15118
 
0.6%
gmelin 12289
 
0.5%
Other values (11309) 2119945
86.9%
2025-01-07T10:48:20.154017image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1853739
 
8.7%
a 1757649
 
8.3%
i 1549698
 
7.3%
s 1388187
 
6.5%
e 1256072
 
5.9%
n 1103662
 
5.2%
r 1034765
 
4.9%
o 978110
 
4.6%
u 968585
 
4.6%
l 964073
 
4.5%
Other values (68) 8406181
39.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21260721
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1853739
 
8.7%
a 1757649
 
8.3%
i 1549698
 
7.3%
s 1388187
 
6.5%
e 1256072
 
5.9%
n 1103662
 
5.2%
r 1034765
 
4.9%
o 978110
 
4.6%
u 968585
 
4.6%
l 964073
 
4.5%
Other values (68) 8406181
39.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21260721
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1853739
 
8.7%
a 1757649
 
8.3%
i 1549698
 
7.3%
s 1388187
 
6.5%
e 1256072
 
5.9%
n 1103662
 
5.2%
r 1034765
 
4.9%
o 978110
 
4.6%
u 968585
 
4.6%
l 964073
 
4.5%
Other values (68) 8406181
39.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21260721
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1853739
 
8.7%
a 1757649
 
8.3%
i 1549698
 
7.3%
s 1388187
 
6.5%
e 1256072
 
5.9%
n 1103662
 
5.2%
r 1034765
 
4.9%
o 978110
 
4.6%
u 968585
 
4.6%
l 964073
 
4.5%
Other values (68) 8406181
39.5%
Distinct22061
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:20.367395image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length65
Median length50
Mean length23.69967259
Min length7

Characters and Unicode

Total characters13854639
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3436 ?
Unique (%)0.6%

Sample

1st rowParoaria capitata
2nd rowRostrhamus sociabilis
3rd rowBartramia longicauda
4th rowSterna hirundo
5th rowPrionochilus plateni
ValueCountFrequency (%)
dendroica 14826
 
1.0%
parus 7485
 
0.5%
melospiza 7103
 
0.5%
turdus 6813
 
0.5%
vireo 6404
 
0.4%
calidris 6376
 
0.4%
sterna 6184
 
0.4%
hyemalis 5963
 
0.4%
melodia 5927
 
0.4%
carduelis 5742
 
0.4%
Other values (10903) 1419872
95.1%
2025-01-07T10:48:20.655087image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1477651
 
10.7%
i 1303096
 
9.4%
s 1190344
 
8.6%
r 934012
 
6.7%
908103
 
6.6%
e 885911
 
6.4%
u 853994
 
6.2%
o 821323
 
5.9%
l 776498
 
5.6%
n 730705
 
5.3%
Other values (48) 3973002
28.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13854639
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1477651
 
10.7%
i 1303096
 
9.4%
s 1190344
 
8.6%
r 934012
 
6.7%
908103
 
6.6%
e 885911
 
6.4%
u 853994
 
6.2%
o 821323
 
5.9%
l 776498
 
5.6%
n 730705
 
5.3%
Other values (48) 3973002
28.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13854639
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1477651
 
10.7%
i 1303096
 
9.4%
s 1190344
 
8.6%
r 934012
 
6.7%
908103
 
6.6%
e 885911
 
6.4%
u 853994
 
6.2%
o 821323
 
5.9%
l 776498
 
5.6%
n 730705
 
5.3%
Other values (48) 3973002
28.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13854639
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1477651
 
10.7%
i 1303096
 
9.4%
s 1190344
 
8.6%
r 934012
 
6.7%
908103
 
6.6%
e 885911
 
6.4%
u 853994
 
6.2%
o 821323
 
5.9%
l 776498
 
5.6%
n 730705
 
5.3%
Other values (48) 3973002
28.7%

typifiedName
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

protocol
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:20.710622image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1753776
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEML
2nd rowEML
3rd rowEML
4th rowEML
5th rowEML
ValueCountFrequency (%)
eml 584592
100.0%
2025-01-07T10:48:20.804036image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 584592
33.3%
M 584592
33.3%
L 584592
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1753776
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 584592
33.3%
M 584592
33.3%
L 584592
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1753776
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 584592
33.3%
M 584592
33.3%
L 584592
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1753776
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 584592
33.3%
M 584592
33.3%
L 584592
33.3%
Distinct183965
Distinct (%)31.5%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:20.941291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.99608616
Min length20

Characters and Unicode

Total characters14027920
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40346 ?
Unique (%)6.9%

Sample

1st row2024-12-02T13:56:05.137Z
2nd row2024-12-02T13:56:08.067Z
3rd row2024-12-02T13:59:48.585Z
4th row2024-12-02T13:56:09.311Z
5th row2024-12-02T13:58:24.805Z
ValueCountFrequency (%)
2024-12-02t13:57:59.341z 17
 
< 0.1%
2024-12-02t13:57:53.841z 16
 
< 0.1%
2024-12-02t13:57:38.028z 16
 
< 0.1%
2024-12-02t13:57:45.007z 16
 
< 0.1%
2024-12-02t13:57:44.964z 15
 
< 0.1%
2024-12-02t13:58:02.554z 15
 
< 0.1%
2024-12-02t13:57:00.688z 15
 
< 0.1%
2024-12-02t13:57:00.663z 15
 
< 0.1%
2024-12-02t13:58:00.792z 15
 
< 0.1%
2024-12-02t13:57:41.116z 15
 
< 0.1%
Other values (183955) 584437
> 99.9%
2025-01-07T10:48:21.158246image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2670609
19.0%
0 1482175
10.6%
1 1475322
10.5%
- 1169184
8.3%
: 1169184
8.3%
4 940152
 
6.7%
5 927783
 
6.6%
3 925430
 
6.6%
T 584592
 
4.2%
Z 584592
 
4.2%
Other values (5) 2098897
15.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14027920
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2670609
19.0%
0 1482175
10.6%
1 1475322
10.5%
- 1169184
8.3%
: 1169184
8.3%
4 940152
 
6.7%
5 927783
 
6.6%
3 925430
 
6.6%
T 584592
 
4.2%
Z 584592
 
4.2%
Other values (5) 2098897
15.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14027920
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2670609
19.0%
0 1482175
10.6%
1 1475322
10.5%
- 1169184
8.3%
: 1169184
8.3%
4 940152
 
6.7%
5 927783
 
6.6%
3 925430
 
6.6%
T 584592
 
4.2%
Z 584592
 
4.2%
Other values (5) 2098897
15.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14027920
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2670609
19.0%
0 1482175
10.6%
1 1475322
10.5%
- 1169184
8.3%
: 1169184
8.3%
4 940152
 
6.7%
5 927783
 
6.6%
3 925430
 
6.6%
T 584592
 
4.2%
Z 584592
 
4.2%
Other values (5) 2098897
15.0%

lastCrawled
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:21.219244image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters14030208
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-12-02T11:48:23.416Z
2nd row2024-12-02T11:48:23.416Z
3rd row2024-12-02T11:48:23.416Z
4th row2024-12-02T11:48:23.416Z
5th row2024-12-02T11:48:23.416Z
ValueCountFrequency (%)
2024-12-02t11:48:23.416z 584592
100.0%
2025-01-07T10:48:21.319100image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2922960
20.8%
1 2338368
16.7%
4 1753776
12.5%
0 1169184
 
8.3%
- 1169184
 
8.3%
: 1169184
 
8.3%
T 584592
 
4.2%
8 584592
 
4.2%
3 584592
 
4.2%
. 584592
 
4.2%
Other values (2) 1169184
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14030208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2922960
20.8%
1 2338368
16.7%
4 1753776
12.5%
0 1169184
 
8.3%
- 1169184
 
8.3%
: 1169184
 
8.3%
T 584592
 
4.2%
8 584592
 
4.2%
3 584592
 
4.2%
. 584592
 
4.2%
Other values (2) 1169184
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14030208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2922960
20.8%
1 2338368
16.7%
4 1753776
12.5%
0 1169184
 
8.3%
- 1169184
 
8.3%
: 1169184
 
8.3%
T 584592
 
4.2%
8 584592
 
4.2%
3 584592
 
4.2%
. 584592
 
4.2%
Other values (2) 1169184
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14030208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2922960
20.8%
1 2338368
16.7%
4 1753776
12.5%
0 1169184
 
8.3%
- 1169184
 
8.3%
: 1169184
 
8.3%
T 584592
 
4.2%
8 584592
 
4.2%
3 584592
 
4.2%
. 584592
 
4.2%
Other values (2) 1169184
 
8.3%
Distinct2
Distinct (%)< 0.1%
Missing3194
Missing (%)0.5%
Memory size4.5 MiB
True
364562 
False
216836 
(Missing)
 
3194
ValueCountFrequency (%)
True 364562
62.4%
False 216836
37.1%
(Missing) 3194
 
0.5%
2025-01-07T10:48:21.371100image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

relativeOrganismQuantity
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

projectId
Unsupported

Missing  Rejected  Unsupported 

Missing584592
Missing (%)100.0%
Memory size4.5 MiB

isSequenced
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size571.0 KiB
False
580105 
True
 
4487
ValueCountFrequency (%)
False 580105
99.2%
True 4487
 
0.8%
2025-01-07T10:48:21.408787image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

gbifRegion
Text

Missing 

Distinct7
Distinct (%)< 0.1%
Missing19462
Missing (%)3.3%
Memory size4.5 MiB
2025-01-07T10:48:21.443294image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length10.62288677
Min length4

Characters and Unicode

Total characters6003312
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLATIN_AMERICA
2nd rowNORTH_AMERICA
3rd rowNORTH_AMERICA
4th rowNORTH_AMERICA
5th rowASIA
ValueCountFrequency (%)
north_america 235097
41.6%
latin_america 161402
28.6%
asia 91675
 
16.2%
africa 47164
 
8.3%
oceania 14385
 
2.5%
europe 13906
 
2.5%
antarctica 1501
 
0.3%
2025-01-07T10:48:21.614871image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1265351
21.1%
I 712626
11.9%
R 694167
11.6%
C 461050
 
7.7%
E 438696
 
7.3%
N 412385
 
6.9%
T 399501
 
6.7%
M 396499
 
6.6%
_ 396499
 
6.6%
O 263388
 
4.4%
Other values (6) 563150
9.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6003312
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 1265351
21.1%
I 712626
11.9%
R 694167
11.6%
C 461050
 
7.7%
E 438696
 
7.3%
N 412385
 
6.9%
T 399501
 
6.7%
M 396499
 
6.6%
_ 396499
 
6.6%
O 263388
 
4.4%
Other values (6) 563150
9.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6003312
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 1265351
21.1%
I 712626
11.9%
R 694167
11.6%
C 461050
 
7.7%
E 438696
 
7.3%
N 412385
 
6.9%
T 399501
 
6.7%
M 396499
 
6.6%
_ 396499
 
6.6%
O 263388
 
4.4%
Other values (6) 563150
9.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6003312
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 1265351
21.1%
I 712626
11.9%
R 694167
11.6%
C 461050
 
7.7%
E 438696
 
7.3%
N 412385
 
6.9%
T 399501
 
6.7%
M 396499
 
6.6%
_ 396499
 
6.6%
O 263388
 
4.4%
Other values (6) 563150
9.4%

publishedByGbifRegion
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-01-07T10:48:21.659849image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters7599696
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNORTH_AMERICA
2nd rowNORTH_AMERICA
3rd rowNORTH_AMERICA
4th rowNORTH_AMERICA
5th rowNORTH_AMERICA
ValueCountFrequency (%)
north_america 584592
100.0%
2025-01-07T10:48:21.757783image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 1169184
15.4%
A 1169184
15.4%
N 584592
7.7%
O 584592
7.7%
T 584592
7.7%
H 584592
7.7%
_ 584592
7.7%
M 584592
7.7%
E 584592
7.7%
I 584592
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7599696
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
R 1169184
15.4%
A 1169184
15.4%
N 584592
7.7%
O 584592
7.7%
T 584592
7.7%
H 584592
7.7%
_ 584592
7.7%
M 584592
7.7%
E 584592
7.7%
I 584592
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7599696
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
R 1169184
15.4%
A 1169184
15.4%
N 584592
7.7%
O 584592
7.7%
T 584592
7.7%
H 584592
7.7%
_ 584592
7.7%
M 584592
7.7%
E 584592
7.7%
I 584592
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7599696
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
R 1169184
15.4%
A 1169184
15.4%
N 584592
7.7%
O 584592
7.7%
T 584592
7.7%
H 584592
7.7%
_ 584592
7.7%
M 584592
7.7%
E 584592
7.7%
I 584592
7.7%

level0Gid
Text

Missing 

Distinct105
Distinct (%)0.5%
Missing562100
Missing (%)96.2%
Memory size4.5 MiB
2025-01-07T10:48:21.856620image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters67476
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)0.1%

Sample

1st rowUSA
2nd rowMYS
3rd rowCOL
4th rowCOL
5th rowIND
ValueCountFrequency (%)
usa 3144
14.0%
eth 2614
 
11.6%
col 2574
 
11.4%
tza 1839
 
8.2%
afg 1717
 
7.6%
rus 826
 
3.7%
per 772
 
3.4%
guy 696
 
3.1%
bra 631
 
2.8%
ven 607
 
2.7%
Other values (95) 7072
31.4%
2025-01-07T10:48:22.000577image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 9076
13.5%
T 5591
 
8.3%
U 5200
 
7.7%
S 4996
 
7.4%
E 4583
 
6.8%
R 4031
 
6.0%
H 3631
 
5.4%
L 3528
 
5.2%
C 3243
 
4.8%
G 3139
 
4.7%
Other values (18) 20458
30.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 67476
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 9076
13.5%
T 5591
 
8.3%
U 5200
 
7.7%
S 4996
 
7.4%
E 4583
 
6.8%
R 4031
 
6.0%
H 3631
 
5.4%
L 3528
 
5.2%
C 3243
 
4.8%
G 3139
 
4.7%
Other values (18) 20458
30.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 67476
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 9076
13.5%
T 5591
 
8.3%
U 5200
 
7.7%
S 4996
 
7.4%
E 4583
 
6.8%
R 4031
 
6.0%
H 3631
 
5.4%
L 3528
 
5.2%
C 3243
 
4.8%
G 3139
 
4.7%
Other values (18) 20458
30.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 67476
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 9076
13.5%
T 5591
 
8.3%
U 5200
 
7.7%
S 4996
 
7.4%
E 4583
 
6.8%
R 4031
 
6.0%
H 3631
 
5.4%
L 3528
 
5.2%
C 3243
 
4.8%
G 3139
 
4.7%
Other values (18) 20458
30.3%

level0Name
Text

Missing 

Distinct105
Distinct (%)0.5%
Missing562100
Missing (%)96.2%
Memory size4.5 MiB
2025-01-07T10:48:22.125909image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length30
Mean length8.545304997
Min length4

Characters and Unicode

Total characters192201
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)0.1%

Sample

1st rowUnited States
2nd rowMalaysia
3rd rowColombia
4th rowColombia
5th rowIndia
ValueCountFrequency (%)
united 3159
 
11.8%
states 3150
 
11.8%
ethiopia 2614
 
9.8%
colombia 2574
 
9.7%
tanzania 1839
 
6.9%
afghanistan 1717
 
6.4%
russia 826
 
3.1%
peru 772
 
2.9%
guyana 696
 
2.6%
brazil 631
 
2.4%
Other values (124) 8681
32.6%
2025-01-07T10:48:22.311051image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 30627
15.9%
i 21547
 
11.2%
n 15591
 
8.1%
t 15171
 
7.9%
e 11832
 
6.2%
o 9996
 
5.2%
s 7991
 
4.2%
l 5975
 
3.1%
h 5409
 
2.8%
d 5050
 
2.6%
Other values (41) 63012
32.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 192201
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 30627
15.9%
i 21547
 
11.2%
n 15591
 
8.1%
t 15171
 
7.9%
e 11832
 
6.2%
o 9996
 
5.2%
s 7991
 
4.2%
l 5975
 
3.1%
h 5409
 
2.8%
d 5050
 
2.6%
Other values (41) 63012
32.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 192201
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 30627
15.9%
i 21547
 
11.2%
n 15591
 
8.1%
t 15171
 
7.9%
e 11832
 
6.2%
o 9996
 
5.2%
s 7991
 
4.2%
l 5975
 
3.1%
h 5409
 
2.8%
d 5050
 
2.6%
Other values (41) 63012
32.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 192201
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 30627
15.9%
i 21547
 
11.2%
n 15591
 
8.1%
t 15171
 
7.9%
e 11832
 
6.2%
o 9996
 
5.2%
s 7991
 
4.2%
l 5975
 
3.1%
h 5409
 
2.8%
d 5050
 
2.6%
Other values (41) 63012
32.8%

level1Gid
Text

Missing 

Distinct474
Distinct (%)2.1%
Missing562129
Missing (%)96.2%
Memory size4.5 MiB
2025-01-07T10:48:22.520603image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.554333793
Min length6

Characters and Unicode

Total characters169693
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)0.5%

Sample

1st rowUSA.49_1
2nd rowMYS.13_1
3rd rowCOL.6_2
4th rowCOL.4_2
5th rowIND.2_1
ValueCountFrequency (%)
eth.8_1 1052
 
4.7%
afg.28_1 995
 
4.4%
usa.2_1 907
 
4.0%
afg.15_1 663
 
3.0%
tza.14_1 573
 
2.6%
eth.4_1 547
 
2.4%
bra.14_1 486
 
2.2%
eth.6_1 475
 
2.1%
per.8_1 473
 
2.1%
kwt.3_1 473
 
2.1%
Other values (464) 15819
70.4%
2025-01-07T10:48:22.794057image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 28607
16.9%
_ 22463
13.2%
. 22443
13.2%
2 9571
 
5.6%
A 9043
 
5.3%
T 5565
 
3.3%
U 5200
 
3.1%
S 4996
 
2.9%
E 4583
 
2.7%
4 4144
 
2.4%
Other values (28) 53078
31.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 169693
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 28607
16.9%
_ 22463
13.2%
. 22443
13.2%
2 9571
 
5.6%
A 9043
 
5.3%
T 5565
 
3.3%
U 5200
 
3.1%
S 4996
 
2.9%
E 4583
 
2.7%
4 4144
 
2.4%
Other values (28) 53078
31.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 169693
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 28607
16.9%
_ 22463
13.2%
. 22443
13.2%
2 9571
 
5.6%
A 9043
 
5.3%
T 5565
 
3.3%
U 5200
 
3.1%
S 4996
 
2.9%
E 4583
 
2.7%
4 4144
 
2.4%
Other values (28) 53078
31.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 169693
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 28607
16.9%
_ 22463
13.2%
. 22443
13.2%
2 9571
 
5.6%
A 9043
 
5.3%
T 5565
 
3.3%
U 5200
 
3.1%
S 4996
 
2.9%
E 4583
 
2.7%
4 4144
 
2.4%
Other values (28) 53078
31.3%

level1Name
Text

Missing 

Distinct464
Distinct (%)2.1%
Missing562129
Missing (%)96.2%
Memory size4.5 MiB
2025-01-07T10:48:23.001229image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length25
Mean length8.892356319
Min length3

Characters and Unicode

Total characters199749
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)0.5%

Sample

1st rowWest Virginia
2nd rowSabah
3rd rowBolívar
4th rowAtlántico
5th rowAndhra Pradesh
ValueCountFrequency (%)
oromia 1052
 
3.7%
parwan 995
 
3.5%
alaska 907
 
3.2%
kandahar 663
 
2.3%
morogoro 573
 
2.0%
benshangul-gumaz 547
 
1.9%
la 528
 
1.8%
pará 486
 
1.7%
peoples 475
 
1.7%
gambela 475
 
1.7%
Other values (530) 22076
76.7%
2025-01-07T10:48:23.265975image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 34856
17.4%
r 15095
 
7.6%
o 12869
 
6.4%
n 12568
 
6.3%
i 10334
 
5.2%
e 9945
 
5.0%
l 7814
 
3.9%
s 7349
 
3.7%
6314
 
3.2%
u 6303
 
3.2%
Other values (71) 76302
38.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 199749
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 34856
17.4%
r 15095
 
7.6%
o 12869
 
6.4%
n 12568
 
6.3%
i 10334
 
5.2%
e 9945
 
5.0%
l 7814
 
3.9%
s 7349
 
3.7%
6314
 
3.2%
u 6303
 
3.2%
Other values (71) 76302
38.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 199749
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 34856
17.4%
r 15095
 
7.6%
o 12869
 
6.4%
n 12568
 
6.3%
i 10334
 
5.2%
e 9945
 
5.0%
l 7814
 
3.9%
s 7349
 
3.7%
6314
 
3.2%
u 6303
 
3.2%
Other values (71) 76302
38.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 199749
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 34856
17.4%
r 15095
 
7.6%
o 12869
 
6.4%
n 12568
 
6.3%
i 10334
 
5.2%
e 9945
 
5.0%
l 7814
 
3.9%
s 7349
 
3.7%
6314
 
3.2%
u 6303
 
3.2%
Other values (71) 76302
38.2%

level2Gid
Text

Missing 

Distinct1023
Distinct (%)4.7%
Missing562935
Missing (%)96.3%
Memory size4.5 MiB
2025-01-07T10:48:23.482551image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.903633929
Min length9

Characters and Unicode

Total characters214483
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique301 ?
Unique (%)1.4%

Sample

1st rowUSA.49.36_1
2nd rowMYS.13.14_1
3rd rowCOL.6.38_2
4th rowCOL.4.9_2
5th rowIND.2.10_1
ValueCountFrequency (%)
afg.28.1_1 995
 
4.6%
afg.15.3_1 663
 
3.1%
eth.4.2_1 547
 
2.5%
eth.8.3_1 515
 
2.4%
eth.6.1_1 475
 
2.2%
per.8.9_1 473
 
2.2%
tza.14.6_1 457
 
2.1%
bra.14.8_2 452
 
2.1%
eth.8.15_1 341
 
1.6%
tza.20.4_1 306
 
1.4%
Other values (1013) 16433
75.9%
2025-01-07T10:48:23.754357image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 43294
20.2%
1 34220
16.0%
_ 21657
 
10.1%
2 15272
 
7.1%
A 8908
 
4.2%
4 6824
 
3.2%
3 6631
 
3.1%
8 5800
 
2.7%
U 5194
 
2.4%
S 4985
 
2.3%
Other values (28) 61698
28.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 214483
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 43294
20.2%
1 34220
16.0%
_ 21657
 
10.1%
2 15272
 
7.1%
A 8908
 
4.2%
4 6824
 
3.2%
3 6631
 
3.1%
8 5800
 
2.7%
U 5194
 
2.4%
S 4985
 
2.3%
Other values (28) 61698
28.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 214483
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 43294
20.2%
1 34220
16.0%
_ 21657
 
10.1%
2 15272
 
7.1%
A 8908
 
4.2%
4 6824
 
3.2%
3 6631
 
3.1%
8 5800
 
2.7%
U 5194
 
2.4%
S 4985
 
2.3%
Other values (28) 61698
28.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 214483
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 43294
20.2%
1 34220
16.0%
_ 21657
 
10.1%
2 15272
 
7.1%
A 8908
 
4.2%
4 6824
 
3.2%
3 6631
 
3.1%
8 5800
 
2.7%
U 5194
 
2.4%
S 4985
 
2.3%
Other values (28) 61698
28.8%

level2Name
Text

Missing 

Distinct991
Distinct (%)4.6%
Missing563182
Missing (%)96.3%
Memory size4.5 MiB
2025-01-07T10:48:23.949345image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length28
Mean length9.567211583
Min length2

Characters and Unicode

Total characters204834
Distinct characters94
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique282 ?
Unique (%)1.3%

Sample

1st rowPendleton
2nd rowPenampang
3rd rowSimití
4th rowManatí
5th rowVisakhapatnam
ValueCountFrequency (%)
bagram 995
 
3.0%
la 771
 
2.3%
rayon 678
 
2.1%
daman 663
 
2.0%
of 606
 
1.8%
kemashi 547
 
1.7%
san 517
 
1.6%
borena 515
 
1.6%
rest 489
 
1.5%
convención 484
 
1.5%
Other values (1170) 26622
80.9%
2025-01-07T10:48:24.210352image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 29287
 
14.3%
o 14241
 
7.0%
n 13826
 
6.7%
e 13296
 
6.5%
i 12566
 
6.1%
r 11826
 
5.8%
11477
 
5.6%
t 8023
 
3.9%
s 6919
 
3.4%
l 6642
 
3.2%
Other values (84) 76731
37.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 204834
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 29287
 
14.3%
o 14241
 
7.0%
n 13826
 
6.7%
e 13296
 
6.5%
i 12566
 
6.1%
r 11826
 
5.8%
11477
 
5.6%
t 8023
 
3.9%
s 6919
 
3.4%
l 6642
 
3.2%
Other values (84) 76731
37.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 204834
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 29287
 
14.3%
o 14241
 
7.0%
n 13826
 
6.7%
e 13296
 
6.5%
i 12566
 
6.1%
r 11826
 
5.8%
11477
 
5.6%
t 8023
 
3.9%
s 6919
 
3.4%
l 6642
 
3.2%
Other values (84) 76731
37.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 204834
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 29287
 
14.3%
o 14241
 
7.0%
n 13826
 
6.7%
e 13296
 
6.5%
i 12566
 
6.1%
r 11826
 
5.8%
11477
 
5.6%
t 8023
 
3.9%
s 6919
 
3.4%
l 6642
 
3.2%
Other values (84) 76731
37.5%

level3Gid
Text

Missing 

Distinct468
Distinct (%)5.1%
Missing575359
Missing (%)98.4%
Memory size4.5 MiB
2025-01-07T10:48:24.421495image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11.89450883
Min length11

Characters and Unicode

Total characters109822
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique169 ?
Unique (%)1.8%

Sample

1st rowIND.2.10.3_1
2nd rowRUS.34.42.1_1
3rd rowTZA.9.4.11_1
4th rowGRC.6.2.16_1
5th rowETH.8.3.1_1
ValueCountFrequency (%)
eth.4.2.2_1 547
 
5.9%
eth.8.3.1_1 499
 
5.4%
eth.6.1.3_1 464
 
5.0%
tza.14.6.4_1 457
 
4.9%
per.8.9.7_1 329
 
3.6%
tza.20.4.4_1 306
 
3.3%
eth.2.3.6_1 289
 
3.1%
eth.8.15.11_1 277
 
3.0%
ind.31.22.2_1 228
 
2.5%
tza.9.4.11_1 203
 
2.2%
Other values (458) 5634
61.0%
2025-01-07T10:48:24.698167image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 27699
25.2%
1 19645
17.9%
_ 9233
 
8.4%
2 5321
 
4.8%
T 4830
 
4.4%
4 4335
 
3.9%
3 4012
 
3.7%
H 3611
 
3.3%
E 3546
 
3.2%
8 2860
 
2.6%
Other values (24) 24730
22.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 109822
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 27699
25.2%
1 19645
17.9%
_ 9233
 
8.4%
2 5321
 
4.8%
T 4830
 
4.4%
4 4335
 
3.9%
3 4012
 
3.7%
H 3611
 
3.3%
E 3546
 
3.2%
8 2860
 
2.6%
Other values (24) 24730
22.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 109822
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 27699
25.2%
1 19645
17.9%
_ 9233
 
8.4%
2 5321
 
4.8%
T 4830
 
4.4%
4 4335
 
3.9%
3 4012
 
3.7%
H 3611
 
3.3%
E 3546
 
3.2%
8 2860
 
2.6%
Other values (24) 24730
22.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 109822
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 27699
25.2%
1 19645
17.9%
_ 9233
 
8.4%
2 5321
 
4.8%
T 4830
 
4.4%
4 4335
 
3.9%
3 4012
 
3.7%
H 3611
 
3.3%
E 3546
 
3.2%
8 2860
 
2.6%
Other values (24) 24730
22.5%

level3Name
Text

Missing 

Distinct441
Distinct (%)5.4%
Missing576369
Missing (%)98.6%
Memory size4.5 MiB
2025-01-07T10:48:24.905017image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length30
Median length24
Mean length8.994041104
Min length3

Characters and Unicode

Total characters73958
Distinct characters85
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique158 ?
Unique (%)1.9%

Sample

1st rowChintapalle
2nd rowKwakoa
3rd rowParanesti
4th rowAbaya
5th rowBio Jiganifado
ValueCountFrequency (%)
jiganifado 547
 
4.8%
bio 547
 
4.8%
abaya 499
 
4.4%
zuria 483
 
4.3%
gambela 464
 
4.1%
hembeti 457
 
4.0%
quimbiri 329
 
2.9%
kisarawe 306
 
2.7%
gewane 289
 
2.5%
lome 277
 
2.4%
Other values (560) 7143
63.0%
2025-01-07T10:48:25.167661image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 11829
16.0%
i 6915
 
9.3%
e 5698
 
7.7%
o 3716
 
5.0%
n 3653
 
4.9%
3118
 
4.2%
r 3027
 
4.1%
m 2665
 
3.6%
u 2447
 
3.3%
b 2389
 
3.2%
Other values (75) 28501
38.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 73958
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 11829
16.0%
i 6915
 
9.3%
e 5698
 
7.7%
o 3716
 
5.0%
n 3653
 
4.9%
3118
 
4.2%
r 3027
 
4.1%
m 2665
 
3.6%
u 2447
 
3.3%
b 2389
 
3.2%
Other values (75) 28501
38.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 73958
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 11829
16.0%
i 6915
 
9.3%
e 5698
 
7.7%
o 3716
 
5.0%
n 3653
 
4.9%
3118
 
4.2%
r 3027
 
4.1%
m 2665
 
3.6%
u 2447
 
3.3%
b 2389
 
3.2%
Other values (75) 28501
38.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 73958
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 11829
16.0%
i 6915
 
9.3%
e 5698
 
7.7%
o 3716
 
5.0%
n 3653
 
4.9%
3118
 
4.2%
r 3027
 
4.1%
m 2665
 
3.6%
u 2447
 
3.3%
b 2389
 
3.2%
Other values (75) 28501
38.5%

iucnRedListCategory
Text

Missing 

Distinct9
Distinct (%)< 0.1%
Missing273793
Missing (%)46.8%
Memory size4.5 MiB
2025-01-07T10:48:25.233528image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters621598
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLC
2nd rowLC
3rd rowLC
4th rowLC
5th rowLC
ValueCountFrequency (%)
lc 259391
83.5%
ne 22703
 
7.3%
nt 14823
 
4.8%
vu 8832
 
2.8%
en 3006
 
1.0%
cr 1367
 
0.4%
ex 575
 
0.2%
dd 71
 
< 0.1%
ew 31
 
< 0.1%
2025-01-07T10:48:25.331522image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 260758
41.9%
L 259391
41.7%
N 40532
 
6.5%
E 26315
 
4.2%
T 14823
 
2.4%
V 8832
 
1.4%
U 8832
 
1.4%
R 1367
 
0.2%
X 575
 
0.1%
D 142
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 621598
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
C 260758
41.9%
L 259391
41.7%
N 40532
 
6.5%
E 26315
 
4.2%
T 14823
 
2.4%
V 8832
 
1.4%
U 8832
 
1.4%
R 1367
 
0.2%
X 575
 
0.1%
D 142
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 621598
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
C 260758
41.9%
L 259391
41.7%
N 40532
 
6.5%
E 26315
 
4.2%
T 14823
 
2.4%
V 8832
 
1.4%
U 8832
 
1.4%
R 1367
 
0.2%
X 575
 
0.1%
D 142
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 621598
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
C 260758
41.9%
L 259391
41.7%
N 40532
 
6.5%
E 26315
 
4.2%
T 14823
 
2.4%
V 8832
 
1.4%
U 8832
 
1.4%
R 1367
 
0.2%
X 575
 
0.1%
D 142
 
< 0.1%